Method and apparatus for csi codebook parameters

ABSTRACT

Apparatuses and methods for channel state information (CSI) codebook parameters. A method performed by a user equipment (UE) includes receiving information about a channel state information (CSI) report, the information indicating N&gt;1 CSI reference signal (CSI-RS) resources and a codebook. The codebook includes a spatial-domain (SD) basis component, a frequency-domain (FD) basis component, and a coefficient component. The SD basis component includes Lr basis vectors for each CSI-RS resource r=1, . . . , N. The FD basis component includes Mv basis vectors. The coefficient component includes coefficients associated with (SD, FD) basis vector pairs. The information includes codebook parameters. The method further includes, based on the information, measuring the N CSI-RS resources; determining, based on the codebook parameters, the SD basis component, the FD basis component, and the coefficient component; and transmitting the CSI report.

CROSS-REFERENCE TO RELATED APPLICATION AND CLAIM OF PRIORITY

This application claims priority under 35 U.S.C. § 119(e) to U.S.Provisional Patent Application No. 63/333,450 filed on Apr. 21, 2022,U.S. Provisional Patent Application No. 63/418,334 filed on Oct. 21,2022, and U.S. Provisional Patent Application No. 63/421,043 filed onOct. 31, 2022. The above-identified provisional patent applications arehereby incorporated by reference in their entirety.

TECHNICAL FIELD

The present disclosure relates generally to wireless communicationsystems and, more specifically, to electronic devices and methods oncodebook parameter configurations for multiple-input multiple-output(MIMO) operations, more particularly, to electronic devices and methodson codebook parameter configurations for distributed MIMO ormulti-transmission reception point (TRP) operations in wirelessnetworks.

BACKGROUND

5th generation (5G) or new radio (NR) mobile communications is recentlygathering increased momentum with all the worldwide technical activitieson the various candidate technologies from industry and academia. Thecandidate enablers for the 5G/NR mobile communications include massiveantenna technologies, from legacy cellular frequency bands up to highfrequencies, to provide beamforming gain and support increased capacity,new waveform (e.g., a new radio access technology (RAT)) to flexiblyaccommodate various services/applications with different requirements,new multiple access schemes to support massive connections, and so on.

SUMMARY

This disclosure relates to apparatuses and methods for CSI codebookparameters.

In one embodiment, a user equipment (UE) is provided. The UE includes atransceiver configured to receive information about a channel stateinformation (CSI) report. The information indicates N>1 CSI referencesignal (CSI-RS) resources and a codebook. The codebook includes aspatial-domain (SD) basis component, a frequency-domain (FD) basiscomponent, and a coefficient component. The SD basis component includesL_(r) basis vectors for each CSI-RS resource r=1, . . . , N. The FDbasis component includes M_(v) basis vectors. The coefficient componentincludes coefficients associated with (SD, FD) basis vector pairs. Theinformation includes codebook parameters. The codebook parametersinclude

$p_{v} = \left\{ \begin{matrix}{{{\frac{1}{8}{for}{\ }v} = 1},2} & \\ & {,\left( {L_{1},L_{2},\ldots,L_{N}} \right),} \\{{{\frac{1}{16}{for}v} = 3},4} & \end{matrix} \right.$

and β where p_(v) is a parameter to determine a value of M based on atotal number of precoding matrices N₃, v is a number of layers, and β≤1is a parameter to determine an upper bound K₀ of a number of non-zerocoefficients of the coefficient component. The UE further includes aprocessor operably coupled to the transceiver. The processor, based onthe information, is configured to measure the N CSI-RS resources anddetermine, based on the codebook parameters, the SD basis component, theFD basis component, and the coefficient component. The transceiver isfurther configured to transmit the CSI report.

In another embodiment, a base station (BS) is provided. The BS includesa processor configured to identify information about a CSI report. Theinformation indicates N>1 CSI-RS resources and a codebook. The codebookincludes a SD basis component, a FD basis component, and a coefficientcomponent. The SD basis component includes L_(r) basis vectors for eachCSI-RS resource r=1, . . . , N. The FD basis component includes M_(v)basis vectors. The coefficient component includes coefficientsassociated with (SD, FD) basis vector pairs. The information includescodebook parameters. The codebook parameters include

$p_{v} = \left\{ {\begin{matrix}{{{\frac{1}{8}{for}v} = 1},2} \\{{{\frac{1}{16}{for}\ v} = 3},4}\end{matrix},\left( {L_{1},L_{2},\ldots,L_{N}} \right),} \right.$

and β. The BS further includes a transceiver operably coupled to theprocessor. The transceiver is configured to transmit the informationabout the CSI report and receive the CSI report.

In yet another embodiment, a method performed by a UE is provided. Themethod includes receiving information about a CSI report. Theinformation indicates N>1 CSI-RS resources and a codebook. The codebookincludes a SD basis component, a FD basis component, and a coefficientcomponent. The SD basis component includes L_(r) basis vectors for eachCSI-RS resource r=1, . . . , N. The FD basis component includes M_(v)basis vectors. The coefficient component includes coefficientsassociated with (SD, FD) basis vector pairs. The information includescodebook parameters. The codebook parameters include

$p_{v} = \left\{ {\begin{matrix}{{{\frac{1}{8}{for}v} = 1},2} \\{{{\frac{1}{16}{for}\ v} = 3},4}\end{matrix},\left( {L_{1},L_{2},\ldots,L_{N}} \right),} \right.$

and β. The method further includes, based on the information, measuringthe N CSI-RS resources; determining, based on the codebook parameters,the SD basis component, the FD basis component, and the coefficientcomponent; and transmitting the CSI report.

Other technical features may be readily apparent to one skilled in theart from the following figures, descriptions, and claims.

Before undertaking the DETAILED DESCRIPTION below, it may beadvantageous to set forth definitions of certain words and phrases usedthroughout this patent document. The term “couple” and its derivativesrefer to any direct or indirect communication between two or moreelements, whether or not those elements are in physical contact with oneanother. The terms “transmit,” “receive,” and “communicate,” as well asderivatives thereof, encompass both direct and indirect communication.The terms “include” and “comprise,” as well as derivatives thereof, meaninclusion without limitation. The term “or” is inclusive, meaningand/or. The phrase “associated with,” as well as derivatives thereof,means to include, be included within, interconnect with, contain, becontained within, connect to or with, couple to or with, be communicablewith, cooperate with, interleave, juxtapose, be proximate to, be boundto or with, have, have a property of, have a relationship to or with, orthe like. The term “controller” means any device, system or part thereofthat controls at least one operation. Such a controller may beimplemented in hardware or a combination of hardware and software and/orfirmware. The functionality associated with any particular controllermay be centralized or distributed, whether locally or remotely. Thephrase “at least one of,” when used with a list of items, means thatdifferent combinations of one or more of the listed items may be used,and only one item in the list may be needed. For example, “at least oneof: A, B, and C” includes any of the following combinations: A, B, C, Aand B, A and C, B and C, and A and B and C.

Moreover, various functions described below can be implemented orsupported by one or more computer programs, each of which is formed fromcomputer readable program code and embodied in a computer readablemedium. The terms “application” and “program” refer to one or morecomputer programs, software components, sets of instructions,procedures, functions, objects, classes, instances, related data, or aportion thereof adapted for implementation in a suitable computerreadable program code. The phrase “computer readable program code”includes any type of computer code, including source code, object code,and executable code. The phrase “computer readable medium” includes anytype of medium capable of being accessed by a computer, such as readonly memory (ROM), random access memory (RAM), a hard disk drive, acompact disc (CD), a digital video disc (DVD), or any other type ofmemory. A “non-transitory” computer readable medium excludes wired,wireless, optical, or other communication links that transporttransitory electrical or other signals. A non-transitory computerreadable medium includes media where data can be permanently stored andmedia where data can be stored and later overwritten, such as arewritable optical disc or an erasable memory device.

Definitions for other certain words and phrases are provided throughoutthis patent document. Those of ordinary skill in the art shouldunderstand that in many if not most instances, such definitions apply toprior as well as future uses of such defined words and phrases.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present disclosure and itsadvantages, reference is now made to the following description taken inconjunction with the accompanying drawings, in which like referencenumerals represent like parts:

FIG. 1 illustrates an example wireless network according to embodimentsof the present disclosure;

FIG. 2 illustrates an example gNodeB (gNB) according to embodiments ofthe present disclosure;

FIG. 3 illustrates an example user equipment (UE) according toembodiments of the present disclosure;

FIG. 4 illustrates an example antenna blocks or arrays forming beamsaccording to embodiments of the present disclosure;

FIG. 5 illustrates an example distributed multiple-input multiple-output(MIMO) system according to embodiments of the present disclosure;

FIG. 6 illustrates an example distributed MIMO system according toembodiments of the present disclosure;

FIG. 7 illustrates an example antenna port layout according toembodiments of the present disclosure;

FIG. 8 illustrates a 3D grid of oversampled discrete Fourier transform(DFT) beams according to embodiments of the present disclosure;

FIG. 9 illustrates two new codebooks according to embodiments of thepresent disclosure; and

FIG. 10 illustrates an example method performed by a UE in a wirelesscommunication system according to embodiments of the present disclosure.

DETAILED DESCRIPTION

FIGS. 1 through 10 , discussed below, and the various embodiments usedto describe the principles of the present disclosure in this patentdocument are by way of illustration only and should not be construed inany way to limit the scope of the disclosure. Those skilled in the artwill understand that the principles of the present disclosure may beimplemented in any suitably-arranged system or device.

The following documents and standards descriptions are herebyincorporated by reference into the present disclosure as if fully setforth herein: 3GPP TS 36.211 v17.2.0, “E-UTRA, Physical channels andmodulation” (herein “REF 1”); 3GPP TS 36.212 v17.2.0, “E-UTRA,Multiplexing and Channel coding” (herein “REF 2”); 3GPP TS 36.213v17.2.0, “E-UTRA, Physical Layer Procedures” (herein “REF 3”); 3GPP TS36.321 v17.1.0, “E-UTRA, Medium Access Control (MAC) protocolspecification” (herein “REF 4”); 3GPP TS 36.331 v17.1.0, “E-UTRA, RadioResource Control (RRC) Protocol Specification” (herein “REF 5”); 3GPP TS38.211 v17.2.0, “NR, Physical channels and modulation” (herein “REF 6”);3GPP TS 38.212 v17.2.0, “NR, Multiplexing and Channel coding” (herein“REF 7”); 3GPP TS 38.213 v17.2.0, “NR, Physical Layer Procedures forControl” (herein “REF 8”); 3GPP TS 38.214 v17.2.0, “NR, Physical LayerProcedures for Data” (herein “REF 9”); 3GPP TS 38.215 v17.1.0, “NR,Physical Layer Measurements” (herein “REF 10”); 3GPP TS 38.321 v17.1.0,“NR, Medium Access Control (MAC) protocol specification” (herein “REF11”); 3GPP TS 38.331 v17.1.0, “NR, Radio Resource Control (RRC) ProtocolSpecification” (herein “REF 12”).

Wireless communication has been one of the most successful innovationsin modern history. Recently, the number of subscribers to wirelesscommunication services exceeded five billion and continues to growquickly. The demand of wireless data traffic is rapidly increasing dueto the growing popularity among consumers and businesses of smart phonesand other mobile data devices, such as tablets, “note pad” computers,net books, eBook readers, and machine type of devices. In order to meetthe high growth in mobile data traffic and support new applications anddeployments, improvements in radio interface efficiency and coverage isof paramount importance.

To meet the demand for wireless data traffic having increased sincedeployment of 4G communication systems and to enable various verticalapplications, 5G/NR communication systems have been developed and arecurrently being deployed. The 5G/NR communication system is consideredto be implemented in higher frequency (mmWave) bands, e.g., 28 GHz or 60GHz bands, so as to accomplish higher data rates or in lower frequencybands, such as 6 GHz, to enable robust coverage and mobility support. Todecrease propagation loss of the radio waves and increase thetransmission distance, the beamforming, massive multiple-inputmultiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna,an analog beam forming, large scale antenna techniques are discussed in5G/NR communication systems.

In addition, in 5G/NR communication systems, development for systemnetwork improvement is under way based on advanced small cells, cloudradio access networks (RANs), ultra-dense networks, device-to-device(D2D) communication, wireless backhaul, moving network, cooperativecommunication, coordinated multi-points (CoMP), reception-endinterference cancelation and the like.

The discussion of 5G systems and frequency bands associated therewith isfor reference as certain embodiments of the present disclosure may beimplemented in 5G systems. However, the present disclosure is notlimited to 5G systems, or the frequency bands associated therewith, andembodiments of the present disclosure may be utilized in connection withany frequency band. For example, aspects of the present disclosure mayalso be applied to deployment of 5G communication systems, 6G or evenlater releases which may use terahertz (THz) bands.

FIGS. 1-3 below describe various embodiments implemented in wirelesscommunications systems and with the use of orthogonal frequency divisionmultiplexing (OFDM) or orthogonal frequency division multiple access(OFDMA) communication techniques. The descriptions of FIGS. 1-3 are notmeant to imply physical or architectural limitations to the manner inwhich different embodiments may be implemented. Different embodiments ofthe present disclosure may be implemented in any suitably arrangedcommunications system.

FIG. 1 illustrates an example wireless network according to embodimentsof the present disclosure. The embodiment of the wireless network shownin FIG. 1 is for illustration only. Other embodiments of the wirelessnetwork 100 could be used without departing from the scope of thisdisclosure.

As shown in FIG. 1 , the wireless network includes a gNB 101 (e.g., basestation, BS), a gNB 102, and a gNB 103. The gNB 101 communicates withthe gNB 102 and the gNB 103. The gNB 101 also communicates with at leastone network 130, such as the Internet, a proprietary Internet Protocol(IP) network, or other data network.

The gNB 102 provides wireless broadband access to the network 130 for afirst plurality of user equipments (UEs) within a coverage area 120 ofthe gNB 102. The first plurality of UEs includes a UE 111, which may belocated in a small business; a UE 112, which may be located in anenterprise; a UE 113, which may be a WiFi hotspot; a UE 114, which maybe located in a first residence; a UE 115, which may be located in asecond residence; and a UE 116, which may be a mobile device, such as acell phone, a wireless laptop, a wireless PDA, or the like. The gNB 103provides wireless broadband access to the network 130 for a secondplurality of UEs within a coverage area 125 of the gNB 103. The secondplurality of UEs includes the UE 115 and the UE 116. In someembodiments, one or more of the gNBs 101-103 may communicate with eachother and with the UEs 111-116 using 5G/NR, long term evolution (LTE),long term evolution-advanced (LTE-A), WiMAX, WiFi, or other wirelesscommunication techniques.

Depending on the network type, the term “base station” or “BS” can referto any component (or collection of components) configured to providewireless access to a network, such as transmit point (TP),transmit-receive point (TRP), an enhanced base station (eNodeB or eNB),a 5G/NR base station (gNB), a macrocell, a femtocell, a WiFi accesspoint (AP), or other wirelessly enabled devices. Base stations mayprovide wireless access in accordance with one or more wirelesscommunication protocols, e.g., 5G/NR 3rd generation partnership project(3GPP) NR, long term evolution (LTE), LTE advanced (LTE-A), high speedpacket access (HSPA), Wi-Fi 802.11a/b/g/n/ac, etc. For the sake ofconvenience, the terms “BS” and “TRP” are used interchangeably in thispatent document to refer to network infrastructure components thatprovide wireless access to remote terminals. Also, depending on thenetwork type, the term “user equipment” or “UE” can refer to anycomponent such as “mobile station,” “subscriber station,” “remoteterminal,” “wireless terminal,” “receive point,” or “user device.” Forthe sake of convenience, the terms “user equipment” and “UE” are used inthis patent document to refer to remote wireless equipment thatwirelessly accesses a BS, whether the UE is a mobile device (such as amobile telephone or smartphone) or is normally considered a stationarydevice (such as a desktop computer or vending machine).

Dotted lines show the approximate extents of the coverage areas 120 and125, which are shown as approximately circular for the purposes ofillustration and explanation only. It should be clearly understood thatthe coverage areas associated with gNBs, such as the coverage areas 120and 125, may have other shapes, including irregular shapes, dependingupon the configuration of the gNBs and variations in the radioenvironment associated with natural and man-made obstructions.

As described in more detail below, one or more of the UEs 111-116include circuitry, programing, or a combination thereof for supportingCSI codebook parameters. In certain embodiments, one or more of the BS s101-103 include circuitry, programing, or a combination thereof forsupporting CSI codebook parameters.

Although FIG. 1 illustrates one example of a wireless network, variouschanges may be made to FIG. 1 . For example, the wireless network couldinclude any number of gNBs and any number of UEs in any suitablearrangement. Also, the gNB 101 could communicate directly with anynumber of UEs and provide those UEs with wireless broadband access tothe network 130. Similarly, each gNB 102-103 could communicate directlywith the network 130 and provide UEs with direct wireless broadbandaccess to the network 130. Further, the gNBs 101, 102, and/or 103 couldprovide access to other or additional external networks, such asexternal telephone networks or other types of data networks.

FIG. 2 illustrates an example gNB 102 according to embodiments of thepresent disclosure. The embodiment of the gNB 102 illustrated in FIG. 2is for illustration only, and the gNBs 101 and 103 of FIG. 1 could havethe same or similar configuration. However, gNBs come in a wide varietyof configurations, and FIG. 2 does not limit the scope of thisdisclosure to any particular implementation of a gNB.

As shown in FIG. 2 , the gNB 102 includes multiple antennas 205 a-205 n,multiple transceivers 210 a-210 n, a controller/processor 225, a memory230, and a backhaul or network interface 235.

The transceivers 210 a-210 n receive, from the antennas 205 a-205 n,incoming RF signals, such as signals transmitted by UEs in the network100. The transceivers 210 a-210 n down-convert the incoming RF signalsto generate IF or baseband signals. The IF or baseband signals areprocessed by receive (RX) processing circuitry in the transceivers 210a-210 n and/or controller/processor 225, which generates processedbaseband signals by filtering, decoding, and/or digitizing the basebandor IF signals. The controller/processor 225 may further process thebaseband signals.

Transmit (TX) processing circuitry in the transceivers 210 a-210 nand/or controller/processor 225 receives analog or digital data (such asvoice data, web data, e-mail, or interactive video game data) from thecontroller/processor 225. The TX processing circuitry encodes,multiplexes, and/or digitizes the outgoing baseband data to generateprocessed baseband or IF signals. The transceivers 210 a-210 nup-converts the baseband or IF signals to RF signals that aretransmitted via the antennas 205 a-205 n.

The controller/processor 225 can include one or more processors or otherprocessing devices that control the overall operation of the gNB 102.For example, the controller/processor 225 could control the reception ofUL channel signals and the transmission of DL channel signals by thetransceivers 210 a-210 n in accordance with well-known principles. Thecontroller/processor 225 could support additional functions as well,such as more advanced wireless communication functions. For instance,the controller/processor 225 could support beam forming or directionalrouting operations in which outgoing/incoming signals from/to multipleantennas 205 a-205 n are weighted differently to effectively steer theoutgoing signals in a desired direction. As another example, thecontroller/processor 225 could support methods for supporting CSIcodebook parameters. Any of a wide variety of other functions could besupported in the gNB 102 by the controller/processor 225.

The controller/processor 225 is also capable of executing programs andother processes resident in the memory 230, such as an OS. Thecontroller/processor 225 can move data into or out of the memory 230 asrequired by an executing process.

The controller/processor 225 is also coupled to the backhaul or networkinterface 235. The backhaul or network interface 235 allows the gNB 102to communicate with other devices or systems over a backhaul connectionor over a network. The interface 235 could support communications overany suitable wired or wireless connection(s). For example, when the gNB102 is implemented as part of a cellular communication system (such asone supporting 5G/NR, LTE, or LTE-A), the interface 235 could allow thegNB 102 to communicate with other gNBs over a wired or wireless backhaulconnection. When the gNB 102 is implemented as an access point, theinterface 235 could allow the gNB 102 to communicate over a wired orwireless local area network or over a wired or wireless connection to alarger network (such as the Internet). The interface 235 includes anysuitable structure supporting communications over a wired or wirelessconnection, such as an Ethernet or transceiver.

The memory 230 is coupled to the controller/processor 225. Part of thememory 230 could include a RAM, and another part of the memory 230 couldinclude a Flash memory or other ROM.

Although FIG. 2 illustrates one example of gNB 102, various changes maybe made to FIG. 2 . For example, the gNB 102 could include any number ofeach component shown in FIG. 2 . Also, various components in FIG. 2could be combined, further subdivided, or omitted and additionalcomponents could be added according to particular needs.

FIG. 3 illustrates an example UE 116 according to embodiments of thepresent disclosure. The embodiment of the UE 116 illustrated in FIG. 3is for illustration only, and the UEs 111-115 of FIG. 1 could have thesame or similar configuration. However, UEs come in a wide variety ofconfigurations, and FIG. 3 does not limit the scope of this disclosureto any particular implementation of a UE.

As shown in FIG. 3 , the UE 116 includes antenna(s) 305, atransceiver(s) 310, and a microphone 320. The UE 116 also includes aspeaker 330, a processor 340, an input/output (I/O) interface (IF) 345,an input 350, a display 355, and a memory 360. The memory 360 includesan operating system (OS) 361 and one or more applications 362.

The transceiver(s) 310 receives, from the antenna 305, an incoming RFsignal transmitted by a gNB of the network 100. The transceiver(s) 310down-converts the incoming RF signal to generate an intermediatefrequency (IF) or baseband signal. The IF or baseband signal isprocessed by RX processing circuitry in the transceiver(s) 310 and/orprocessor 340, which generates a processed baseband signal by filtering,decoding, and/or digitizing the baseband or IF signal. The RX processingcircuitry sends the processed baseband signal to the speaker 330 (suchas for voice data) or is processed by the processor 340 (such as for webbrowsing data).

TX processing circuitry in the transceiver(s) 310 and/or processor 340receives analog or digital voice data from the microphone 320 or otheroutgoing baseband data (such as web data, e-mail, or interactive videogame data) from the processor 340. The TX processing circuitry encodes,multiplexes, and/or digitizes the outgoing baseband data to generate aprocessed baseband or IF signal. The transceiver(s) 310 up-converts thebaseband or IF signal to an RF signal that is transmitted via theantenna(s) 305.

The processor 340 can include one or more processors or other processingdevices and execute the OS 361 stored in the memory 360 in order tocontrol the overall operation of the UE 116. For example, the processor340 could control the reception of DL channel signals and thetransmission of UL channel signals by the transceiver(s) 310 inaccordance with well-known principles. In some embodiments, theprocessor 340 includes at least one microprocessor or microcontroller.

The processor 340 is also capable of executing other processes andprograms resident in the memory 360. The processor 340 can move datainto or out of the memory 360 as required by an executing process. Insome embodiments, the processor 340 is configured to execute theapplications 362 based on the OS 361 or in response to signals receivedfrom gNBs or an operator. The processor 340 is also coupled to the I/Ointerface 345, which provides the UE 116 with the ability to connect toother devices, such as laptop computers and handheld computers. The I/Ointerface 345 is the communication path between these accessories andthe processor 340.

The processor 340 is also coupled to the input 350, which includes forexample, a touchscreen, keypad, etc., and the display 355. The operatorof the UE 116 can use the input 350 to enter data into the UE 116. Thedisplay 355 may be a liquid crystal display, light emitting diodedisplay, or other display capable of rendering text and/or at leastlimited graphics, such as from web sites.

The memory 360 is coupled to the processor 340. Part of the memory 360could include a random-access memory (RAM), and another part of thememory 360 could include a Flash memory or other read-only memory (ROM).

Although FIG. 3 illustrates one example of UE 116, various changes maybe made to FIG. 3 . For example, various components in FIG. 3 could becombined, further subdivided, or omitted and additional components couldbe added according to particular needs. As a particular example, theprocessor 340 could be divided into multiple processors, such as one ormore central processing units (CPUs) and one or more graphics processingunits (GPUs). In another example, the transceiver(s) 310 may include anynumber of transceivers and signal processing chains and may be connectedto any number of antennas. Also, while FIG. 3 illustrates the UE 116configured as a mobile telephone or smartphone, UEs could be configuredto operate as other types of mobile or stationary devices.

The 3GPP NR specification supports up to 32 CSI-RS antenna ports whichenable a gNB to be equipped with a large number of antenna elements(such as 64 or 128). In this case, a plurality of antenna elements ismapped onto one CSI-RS port. For next generation cellular systems suchas 5G, the maximum number of CSI-RS ports can either remain the same orincrease.

FIG. 4 illustrates an example antenna blocks or arrays 400 according toembodiments of the present disclosure. The embodiment of the antennablocks or arrays 400 illustrated in FIG. 4 is for illustration only.FIG. 4 does not limit the scope of this disclosure to any particularimplementation of the antenna blocks or arrays.

For mmWave bands, although the number of antenna elements can be largerfor a given form factor, the number of CSI-RS ports—which can correspondto the number of digitally precoded ports—tends to be limited due tohardware constraints (such as the feasibility to install a large numberof ADCs/DACs at mmWave frequencies) as illustrated in FIG. 4 . In thiscase, one CSI-RS port is mapped onto a large number of antenna elementswhich can be controlled by a bank of analog phase shifters 401. OneCSI-RS port can then correspond to one sub-array which produces a narrowanalog beam through analog beamforming 405. This analog beam can beconfigured to sweep across a wider range of angles 420 by varying thephase shifter bank across symbols or subframes. The number of sub-arrays(equal to the number of RF chains) is the same as the number of CSI-RSports NCSI-PORT A digital beamforming unit 410 performs a linearcombination across NCSI-PORT analog beams to further increase precodinggain. While analog beams are wideband (hence not frequency-selective),digital precoding can be varied across frequency sub-bands or resourceblocks. Receiver operation can be conceived analogously.

Since the above system utilizes multiple analog beams for transmissionand reception (wherein one or a small number of analog beams areselected out of a large number, for instance, after a trainingduration—to be performed from time to time), the term “multi-beamoperation” is used to refer to the overall system aspect. This includes,for the purpose of illustration, indicating the assigned DL or ULtransmit (TX) beam (also termed “beam indication”), measuring at leastone reference signal for calculating and performing beam reporting (alsotermed “beam measurement” and “beam reporting”, respectively), andreceiving a DL or UL transmission via a selection of a correspondingreceive (RX) beam.

The above system is also applicable to higher frequency bands suchas >52.6 GHz (also termed the FR4). In this case, the system can employonly analog beams. Due to the O2 absorption loss around 60 GHz frequency(˜10 dB additional loss @ 100 m distance), larger number of and sharperanalog beams (hence larger number of radiators in the array) will beneeded to compensate for the additional path loss.

At lower frequency bands such as <1 GHz, on the other hand, the numberof antenna elements may not be large in a given form factor due to thelarge wavelength. As an example, for the case of the wavelength size (λ)of the center frequency 600 MHz (which is 50 cm), it desires 4 m foruniform-linear-array (ULA) antenna panel of 16 antenna elements with thehalf-wavelength distance between two adjacent antenna elements.Considering a plurality of antenna elements is mapped to one digitalport in practical cases, the desirable size for antenna panel(s) at gNBto support a large number of antenna ports such as 32 CSI-RS portsbecomes very large in such low frequency bands, and it leads thedifficulty of deploying 2-D antenna element arrays within the size of aconventional form factor. This results in a limited number of CSI-RSports that can be supported at a single site and limits the spectralefficiency of such systems.

Various embodiments of the present disclosure recognize that for acellular system operating in a sub-1 GHz frequency range (e.g., lessthan 1 GHz), supporting large number of CSI-RS antenna ports (e.g., 32)at a single location or remote radio head (RRH) or TRP is challengingdue to that a larger antenna form factor size is needed at thesefrequencies than a system operating at a higher frequency such as 2 GHzor 4 GHz. At such low frequencies, the maximum number of CSI-RS antennaports that can be co-located at a single site (or TRP/RRH) can belimited, for example to 8. This limits the spectral efficiency of suchsystems. In particular, the MU-MIMO spatial multiplexing gains offereddue to large number of CSI-RS antenna ports (such as 32) can't beachieved.

One way to operate a sub-1 GHz system with a large number of CSI-RSantenna ports is based on distributing antenna ports at multiplelocations (or TRP/RRHs). The multiple sites or TRPs/RRHs can still beconnected to a single (common) base unit, hence the signaltransmitted/received via multiple distributed TRPs/RRHs can still beprocessed at a centralized location. This is called distributed MIMO ormulti-TRP coherent joint transmission (C-JT).

Accordingly, various embodiments of the present disclosure consider themulti-TRP C-JT scenario and propose methods and apparatus for codebookparameters considering feedback overhead in the scenario.

Various embodiments of the present disclosure recognize that CSIenhancement described in Rel-18 MIMO considers Rel-16/17 Type-II CSIcodebook refinements to support mTRP coherent joint transmission (C-JT)operations by considering performance-and-overhead trade-off. TheRel-16/17 Type-II CSI codebook has three components W₁, W₂, and W_(f).Among them, W₂ is the component that could induce large CSI feedbackoverhead especially in mTRP C-JT operations.

Accordingly, various embodiments of the present disclosure providecodebook parameter configurations to alleviate the amount of CSIreporting overhead to have good performance-and-overhead trade-off forC-JT operations. The codebook parameter configurations (an extension ofthe tables of paraCombination-r16, paraCombination-r17) are proposed tohave good performance-and-overhead trade-off for mTRP C-JT operations.

FIG. 5 illustrates an example distributed MIMO system 500 according toembodiments of the present disclosure. The embodiment of the distributedMIMO system 500 illustrated in FIG. 5 is for illustration only. FIG. 5does not limit the scope of this disclosure to any particularimplementation of the distributed MIMO system 500.

One possible approach to resolving the issue is to form multiple TRPs(multi-TRP) or RRHs with a small number of antenna ports instead ofintegrating all of the antenna ports in a single panel (or at a singlesite) and to distribute the multiple panels in multiple locations/sites(or TRPs, RRHs). This approach is shown in FIG. 5 .

FIG. 6 illustrates an example distributed MIMO system 600 according toembodiments of the present disclosure. The embodiment of the distributedMIMO system 600 illustrated in FIG. 6 is for illustration only. FIG. 6does not limit the scope of this disclosure to any particularimplementation of the distributed MIMO system 600.

As illustrated in FIG. 6 , the multiple TRPs at multiple locations canstill be connected to a single base unit, and thus the signaltransmitted/received via multiple distributed TRPs can be processed in acentralized manner through the single base unit.

Note that although the present disclosure has mentioned low frequencyband systems (sub-1 GHz band) as a motivation for distributed MIMO (ormTRP), the distributed MIMO technology is frequency-band-agnostic andcan be useful in mid-(sub-6 GHz) and high-band (above-6 GHz) systems inaddition to low-band (sub-1 GHz) systems.

The terminology “distributed MIMO” is used as an illustrative purpose,it can be considered under another terminology such as multi-TRP, mTRP,cell-free network, and so on.

All the following components and embodiments are applicable for ULtransmission with CP-OFDM (cyclic prefix OFDM) waveform as well asDFT-SOFDM (DFT-spread OFDM) and SC-FDMA (single-carrier FDMA) waveforms.Furthermore, all the following components and embodiments are applicablefor UL transmission when the scheduling unit in time is either onesubframe (which can consist of one or multiple slots) or one slot.

In the present disclosure, the frequency resolution (reportinggranularity) and span (reporting bandwidth) of CSI reporting can bedefined in terms of frequency “subbands” and “CSI reporting band” (CRB),respectively.

A subband for CSI reporting is defined as a set of contiguous PRBs whichrepresents the smallest frequency unit for CSI reporting. The number ofPRBs in a subband can be fixed for a given value of DL system bandwidth,configured either semi-statically via higher-layer/RRC signaling, ordynamically via L1 DL control signaling or MAC control element (MAC CE).The number of PRBs in a subband can be included in CSI reportingsetting.

“CSI reporting band” is defined as a set/collection of subbands, eithercontiguous or non-contiguous, wherein CSI reporting is performed. Forexample, CSI reporting band can include all the subbands within the DLsystem bandwidth. This can also be termed “full-band”. Alternatively,CSI reporting band can include only a collection of subbands within theDL system bandwidth. This can also be termed “partial band”.

The term “CSI reporting band” is used only as an example forrepresenting a function. Other terms such as “CSI reporting subband set”or “CSI reporting bandwidth” can also be used.

In terms of UE configuration, a UE can be configured with at least oneCSI reporting band. This configuration can be semi-static (viahigher-layer signaling or RRC) or dynamic (via MAC CE or L1 DL controlsignaling). When configured with multiple (N) CSI reporting bands (e.g.,via RRC signaling), a UE can report CSI associated with n≤N CSIreporting bands. For instance, >6 GHz, large system bandwidth mayrequire multiple CSI reporting bands. The value of n can either beconfigured semi-statically (via higher-layer signaling or RRC) ordynamically (via MAC CE or L1 DL control signaling). Alternatively, theUE can report a recommended value of n via an UL channel.

Therefore, CSI parameter frequency granularity can be defined per CSIreporting band as follows. A CSI parameter is configured with “single”reporting for the CSI reporting band with M_(n) subbands when one CSIparameter for all the M_(n) subbands within the CSI reporting band. ACSI parameter is configured with “subband” for the CSI reporting bandwith M_(n) subbands when one CSI parameter is reported for each of theM_(n) subbands within the CSI reporting band.

FIG. 7 illustrates an example antenna port layout 700 according toembodiments of the present disclosure. The embodiment of the antennaport layout 700 illustrated in FIG. 13 is for illustration only. FIG. 7does not limit the scope of this disclosure to any particularimplementation of the antenna port layout.

As illustrated in FIG. 7 , N₁ and N₂ are the number of antenna portswith the same polarization in the first and second dimensions,respectively. For 2D antenna port layouts, N₁>1, N₂>1, and for 1Dantenna port layouts N₁>1 and N₂=1. Therefore, for a dual-polarizedantenna port layout, the total number of antenna ports is 2N₁N₂ wheneach antenna maps to an antenna port. An illustration is shown in FIG. 7where “X” represents two antenna polarizations. In this disclosure, theterm “polarization” refers to a group of antenna ports. For example,antenna ports

${j = {X + 0}},{X + 1},\ldots,{X + \frac{P_{CSIRS}}{2} - 1}$

comprise a first antenna polarization, and antenna ports

${j = {X + \frac{P_{CSIRS}}{2}}},{X + \frac{P_{CSIRS}}{2} + 1},\ldots,{X + P_{CSIRS} - 1}$

comprise a second antenna polarization, where P_(CSIRS) is a number ofCSI-RS antenna ports and X is a starting antenna port number (e.g.,X=3000, then antenna ports are 3000, 3001, 3002, . . . ). Let N_(g) be anumber of antenna panels at the gNB. When there are multiple antennapanels (N_(g)>1), we assume that each panel is dual-polarized antennaports with N₁ and N₂ ports in two dimensions. This is illustrated inFIG. 7 . Note that the antenna port layouts may or may not be the samein different antenna panels.

In one example, the antenna architecture of a D-MIMO or CJT (coherentjoint-transmission) system is structured. For example, the antennastructure at each RRH (or TRP) is dual-polarized (single or multi-panelas shown in FIG. 7 . The antenna structure at each RRH/TRP can be thesame. Alternatively, the antenna structure at an RRH/TRP can bedifferent from another RRH/TRP. Likewise, the number of ports at eachRRH/TRP can be the same. Alternatively, the number of ports at oneRRH/TRP can be different from another RRH/TRP. In one example,N_(g)=N_(RRH), a number of RRHs/TRPs in the D-MIMO transmission.

In another example, the antenna architecture of a D-MIMO or CJT systemis unstructured. For example, the antenna structure at one RRH/TRP canbe different from another RRH/TRP.

We assume a structured antenna architecture in the rest of thedisclosure. For simplicity, we assume each RRH/TRP is equivalent to apanel, although, an RRH/TRP can have multiple panels in practice. Thedisclosure however is not restrictive to a single panel assumption ateach RRH/TRP, and can easily be extended (covers) the case when anRRH/TRP has multiple antenna panels.

In one embodiment, an RRH constitutes (or corresponds to or isequivalent to) at least one of the following:

-   -   In one example, an RRH corresponds to a TRP.    -   In one example, an RRH or TRP corresponds to a CSI-RS resource.        A UE is configured with K=N_(RRH)>1 non-zero-power (NZP) CSI-RS        resources, and a CSI reporting is configured to be across        multiple CSI-RS resources. This is similar to Class B, K>1        configuration in Rel. 14 LTE. The K NZP CSI-RS resources can        belong to a CSI-RS resource set or multiple CSI-RS resource sets        (e.g., K resource sets each comprising one CSI-RS resource). The        details are as explained earlier in this disclosure.    -   In one example, an RRH or TRP corresponds to a CSI-RS resource        group, where a group comprises one or multiple NZP CSI-RS        resources. A UE is configured with K≥N_(RRH)>1 non-zero-power        (NZP) CSI-RS resources, and a CSI reporting is configured to be        across multiple CSI-RS resources from resource groups. This is        similar to Class B, K>1 configuration in Rel. 14 LTE. The K NZP        CSI-RS resources can belong to a CSI-RS resource set or multiple        CSI-RS resource sets (e.g., K resource sets each comprising one        CSI-RS resource). The details are as explained earlier in this        disclosure. In particular, the K CSI-RS resources can be        partitioned into N_(RRH) resource groups. The information about        the resource grouping can be provided together with the CSI-RS        resource setting/configuration, or with the CSI reporting        setting/configuration, or with the CSI-RS resource        configuration.    -   In one example, an RRH or TRP corresponds to a subset (or a        group) of CSI-RS ports. A UE is configured with at least one NZP        CSI-RS resource comprising (or associated with) CSI-RS ports        that can be grouped (or partitioned) multiple        subsets/groups/parts of antenna ports, each corresponding to (or        constituting) an RRH/TRP. The information about the subsets of        ports or grouping of ports can be provided together with the        CSI-RS resource setting/configuration, or with the CSI reporting        setting/configuration, or with the CSI-RS resource        configuration.    -   In one example, an RRH or TRP corresponds to one or more        examples described above depending on a configuration. For        example, this configuration can be explicit via a parameter        (e.g., an RRC parameter). Alternatively, it can be implicit.        -   In one example, when implicit, it could be based on the            value of K. For example, when K>1 CSI-RS resources, an RRH            corresponds to one or more examples described above, and            when K=1 CSI-RS resource, an RRH corresponds to one or more            examples described above.        -   In another example, the configuration could be based on the            configured codebook. For example, an RRH corresponds to a            CSI-RS resource or resource group when the codebook            corresponds to a decoupled codebook (modular or separate            codebook for each RRH), and an RRH corresponds to a subset            (or a group) of CSI-RS ports when codebook corresponds to a            coupled (joint or coherent) codebook (one joint codebook            across TRPs/RRHs).

In one example, when RRH or TRP maps (or corresponds to) a CSI-RSresource or resource group, and a UE can select a subset of RRHs(resources or resource groups) and report the CSI for the selectedTRPs/RRHs (resources or resource groups), the selected TRPs/RRHs can bereported via an indicator. For example, the indicator can be a CRI or aPMI (component) or a new indicator.

In one example, when RRH or TRP maps (or corresponds to) a CSI-RS portgroup, and a UE can select a subset of TRPs/RRHs (port groups) andreport the CSI for the selected TRPs/RRHs (port groups), the selectedTRPs/RRHs can be reported via an indicator. For example, the indicatorcan be a CRI or a PMI (component) or a new indicator.

In one example, when multiple (K>1) CSI-RS resources are configured forN_(RRH) TRPs/RRHs, a decoupled (modular) codebook is used/configured,and when a single (K=1) CSI-RS resource for N_(RRH) TRPs/RRHs, a jointcodebook is used/configured.

As described in U.S. Pat. No. 10,659,118, issued May 19, 2020, andentitled “Method and Apparatus for Explicit CSI Reporting in AdvancedWireless Communication Systems,” which is incorporated herein byreference in its entirety, a UE is configured with high-resolution(e.g., Type II) CSI reporting in which the linear combination-based TypeII CSI reporting framework is extended to include a frequency dimensionin addition to the first and second antenna port dimensions.

FIG. 8 illustrates a 3D grid of oversampled DFT beams 800 according toembodiments of the present disclosure. The embodiment of the 3D grid ofoversampled DFT beams 800 illustrated in FIG. 8 is for illustrationonly. FIG. 8 does not limit the scope of this disclosure to anyparticular implementation of the 3D grid of oversampled DFT beams.

As illustrated, FIG. 8 shows a 3D grid 800 of the oversampled DFT beams(1st port dim., 2nd port dim., freq. dim.) in which:

-   -   a 1st dimension is associated with the 1st port dimension,    -   a 2nd dimension is associated with the 2nd port dimension, and    -   a 3rd dimension is associated with the frequency dimension.

The basis sets for 1^(st) and 2^(nd) port domain representation areoversampled DFT codebooks of length-N₁ and length-N₂, respectively, andwith oversampling factors O₁ and O₂, respectively. Likewise, the basisset for frequency domain representation (i.e., 3rd dimension) is anoversampled DFT codebook of length-N₃ and with oversampling factor O₃.In one example, O₁=O₂=O₃=4. In one example, O₁=O₂=4 and O₃=1. In anotherexample, the oversampling factors O_(i) belongs to {2, 4, 8}. In yetanother example, at least one of O₁, O₂, and O₃ is higher layerconfigured (via RRC signaling).

As explained in Section 5.2.2.2.6 of REFS, a UE is configured withhigher layer parameter codebookType set to ‘ typeII-PortSelection-r16’for an enhanced Type II CSI reporting in which the pre-coders for allSBs and for a given layer l=1, . . . , v, where v is the associated RIvalue, is given by either

$\begin{matrix}{{W^{l} = {{{AC}_{l}B^{H}} = \left\lbrack {a_{0}a_{1}\ \ldots\ a_{L - 1}} \right\rbrack}}{{{\begin{bmatrix}c_{l,0,0} & c_{l,0,1} & \ldots & c_{l,0,{M - 1}} \\c_{l,1,0} & c_{l,1,1} & \ldots & c_{l,1,{M - 1}} \\ \vdots & \vdots & \vdots & \vdots \\c_{l,{L - 1},0} & c_{l,{L - 1},1} & \ldots & c_{l,{L - 1},{M - 1}}\end{bmatrix}\left\lbrack {b_{0}b_{1}\ \ldots\ b_{M - 1}} \right\rbrack}^{H} = {{\Sigma_{f = 0}^{M - 1}\Sigma_{i = 0}^{L - 1}{c_{l,i,f}\left( {a_{i}b_{f}^{H}} \right)}} = {\Sigma_{i = 0}^{L - 1}\Sigma_{f = 0}^{M - 1}{c_{l,i,f}\left( {a_{i}b_{f}^{H}} \right)}}}},}} & \left( {{Eq}.1} \right)\end{matrix}$ or $\begin{matrix}{{W^{l} = {{\begin{bmatrix}A & 0 \\0 & A\end{bmatrix}\ C_{l}B^{H}} = \begin{bmatrix}{a_{0}a_{1}\ldots a_{L - 1}} & 0 \\0 & {a_{0}a_{1}\ldots a_{L - 1}}\end{bmatrix}}}{{{\begin{bmatrix}c_{l,0,0} & c_{l,0,1} & \ldots & c_{l,0,{M - 1}} \\c_{l,1,0} & c_{l,1,1} & \ldots & c_{l,1,{M - 1}} \\ \vdots & \vdots & \vdots & \vdots \\c_{l,{L - 1},0} & c_{l,{L - 1},1} & \ldots & c_{l,{L - 1},{M - 1}}\end{bmatrix}\left\lbrack {b_{0}b_{1}\ \ldots\ b_{M - 1}} \right\rbrack}^{H} = {{\begin{bmatrix}{\Sigma_{f = 0}^{M - 1}\Sigma_{i = 0}^{L - 1}c_{l,i,f}\left( {a_{i}b_{f}^{H}} \right)} \\{\Sigma_{f = 0}^{M - 1}\Sigma_{i = 0}^{L - 1}c_{l,{i + L},f}\left( {a_{i}b_{f}^{H}} \right)}\end{bmatrix},}}}}} & \left( {{Eq}.2} \right)\end{matrix}$

where:

-   -   N₁ is a number of antenna ports in a first antenna port        dimension (having the same antenna polarization),    -   N₂ is a number of antenna ports in a second antenna port        dimension (having the same antenna polarization), P_(CSI-RS) is        a number of CSI-RS ports configured to the UE,    -   N₃ is a number of SBs for PMI reporting or number of FD units or        number of FD components (that comprise the CSI reporting band)        or a total number of precoding matrices indicated by the PMI        (one for each FD unit/component),    -   α₁ is a 2N₁N₂×1 (Eq. 1) or N₁N₂×1 (Eq. 2) column vector, or        α_(i) is a

$\begin{matrix}{P_{CSIRS} \times 1} & \left( {{Eq}.1} \right)\end{matrix}$ ${or}\frac{P_{CSIRS}}{2} \times 1$

-   -    port selection column vector, where a port selection vector is        a defined as a vector which contains a value of 1 in one element        and zeros elsewhere,    -   b_(f) is a N₃×1 column vector,    -   c_(l,i,f) is a complex coefficient.

In a variation, when the UE reports a subset K<2LM coefficients (where Kis either fixed, configured by the gNB or reported by the UE), then thecoefficient c_(l,i,f) in precoder equations Eq. 1 or Eq. 2 is replacedwith x_(l,i,f)×c_(l,i,f), where:

-   -   x_(l,i,f)=1 if the coefficient c_(l,i,f) is reported by the UE        according to some embodiments of this disclosure.    -   x_(l,i,f)=0 otherwise (i.e., c_(l,i,f) is not reported by the        UE).

The indication whether x_(l,i,f)=1 or 0 is according to some embodimentsof this disclosure. For example, it can be via a bitmap.

In a variation, the precoder equations Eq. 1 or Eq. 2 are respectivelygeneralized to

$\begin{matrix}{W^{l} = {\Sigma_{i = 0}^{L - 1}\Sigma_{f = 0}^{M_{i} - 1}{c_{l,i,f}\left( {a_{i}b_{i,f}^{H}} \right)}}} & \left( {{Eq}.3} \right)\end{matrix}$ and $\begin{matrix}{{W^{l} = \begin{bmatrix}{\Sigma_{i = 0}^{L - 1}\Sigma_{f = 0}^{M_{i} - 1}{c_{l,i,f}\left( {a_{i}b_{i,f}^{H}} \right)}} \\{\Sigma_{i = 0}^{L - 1}\Sigma_{= 0}^{M_{i} - 1}{c_{l,{i + L},f}\left( {a_{i}b_{i,f}^{H}} \right)}}\end{bmatrix}},} & \left( {{Eq}.4} \right)\end{matrix}$

where for a given i, the number of basis vectors is M_(i) and thecorresponding basis vectors are {b_(i,f)}. Note that M_(i) is the numberof coefficients c_(l,i,f) reported by the UE for a given i, whereM_(i)≤M (where {M_(i)} or ΣM_(i) is either fixed, configured by the gNBor reported by the UE).

The columns of W¹ are normalized to norm one. For rank R or R layers(υ=R), the pre-coding matrix is given by

${{L \leq {\frac{P_{{CSI} - {RS}}}{2}{and}M} \leq {{N_{3}.{If}}L}} = \frac{P_{{CSI} - {RS}}}{2}},$

Eq. 2 is assumed in the rest of the disclosure. The embodiments of thedisclosure, however, are general and are also application to Eq. 1, Eq.3, and Eq. 4.

Here

$W^{(R)} = {{\frac{1}{\sqrt{R}}\left\lbrack {W^{1}W^{2}\ldots W^{R}} \right\rbrack}.}$

then A is an identity matrix, and hence not reported. Likewise, if M=N₃,then B is an identity matrix, and hence not reported. Assuming M<N₃, inan example, to report columns of B, the oversampled DFT codebook isused. For instance, b_(f)=w_(f), where the quantity w_(f) is given by

$w_{f} = {\left\lbrack {1e^{j\frac{2\pi n_{3,l}^{(f)}}{O_{3}N_{3}}}e^{j\frac{2{\pi \cdot 2}n_{3,l}^{(f)}}{O_{3}N_{3}}}\ldots e^{j\frac{2{\pi \cdot {({N_{3} - 1})}}n_{3,l}^{(f)}}{O_{3}N_{3}}}} \right\rbrack^{T}.}$

When O₃=1, the FD basis vector for layer l∈{1, . . . , υ} (where v isthe RI or rank value) is given by:

w_(f) = [y_(0, l)^((f))y_(1, l)^((f))…y_(N₃ − 1, l)^((f))]^(T), where$y_{t,l}^{(f)} = {{e^{j\frac{2\pi{tn}_{3,l}^{(f)}}{N_{3}}}{and}n_{3,l}} = \left\lbrack {n_{3,l}^{(0)},\ldots,n_{3,l}^{({M - 1})}} \right\rbrack}$where n_(3, l)^((f)) ∈ {0, 1, …, N₃ − 1}.

In another example, discrete cosine transform DCT basis is used toconstruct/report basis B for the 3^(rd) dimension. The m-th column ofthe DCT compression matrix is simply given by:

$\left\lbrack w_{f} \right\rbrack_{nm} = \left\{ {\begin{matrix}{\frac{1}{\sqrt{K}},{n = 0}} \\{{\sqrt{\frac{2}{K}}\cos\frac{{\pi\left( {{2m} + 1} \right)}n}{2K}},\ {n = 1},{{\ldots\ K} - 1}}\end{matrix},{and}} \right.$ K = N₃, andm = 0, …, N₃ − 1.

Since DCT is applied to real valued coefficients, the DCT is applied tothe real and imaginary components (of the channel or channeleigenvectors) separately. Alternatively, the DCT is applied to themagnitude and phase components (of the channel or channel eigenvectors)separately. The use of DFT or DCT basis is for illustration purposesonly. The disclosure is applicable to any other basis vectors toconstruct/report A and B.

On a high level, a precoder W^(l) can be described as follows.

W=A _(l) C _(l) B _(l) ^(H) =W ₁ {tilde over (W)} ₂ W _(f) ^(H),  (Eq.5)

where A=W₁ corresponds to the Rel. 15 W₁ in Type II CSI codebook [REFS],and B=W_(f).

The C_(l)={tilde over (W)}₂ matrix consists of all the required linearcombination coefficients (e.g., amplitude and phase or real orimaginary). Each reported coefficient (c_(l,i,f)=p_(l,i,f)ϕ_(l,i,f)) inW₂ is quantized as amplitude coefficient (p_(l,i,f)) and phasecoefficient (ϕ_(l,i,f)). In one example, the amplitude coefficient(p_(l,i,f)) is reported using a A-bit amplitude codebook where A belongsto {2, 3, 4}. If multiple values for A are supported, then one value isconfigured via higher layer signaling. In another example, the amplitudecoefficient (P_(l,i,f)) is reported as P_(l,i,f)=p_(l,i,f) ⁽¹⁾p_(l,i,f)⁽²⁾ where:

-   -   p_(l,i,f) ⁽¹⁾ is a reference or first amplitude which is        reported using an A1-bit amplitude codebook where A1 belongs to        {2, 3, 4}, and    -   p_(l,i,f) ⁽²⁾ is a differential or second amplitude which is        reported using a A2-bit amplitude codebook where A2≤A1 belongs        to {2, 3, 4}.

For layer l, let us denote the linear combination (LC) coefficientassociated with spatial domain (SD) basis vector (or beam) i∈{0, 1, . .. , 2L−1} and frequency domain (FD) basis vector (or beam) f∈{0, 1, . .. , M−1} as c_(l,i,f), and the strongest coefficient as. The strongestcoefficient is reported out of the K_(NZ) non-zero (NZ) coefficientsthat is reported using a bitmap, where K_(NZ)≤K₀=┌β×2LM┐<2LM and β ishigher layer configured. The remaining 2LM−K_(NZ) coefficients that arenot reported by the UE are assumed to be zero. The followingquantization scheme is used to quantize/report the K_(NZ) NZcoefficients.

-   -   UE reports the following for the quantization of the NZ        coefficients in {tilde over (W)}₂        -   A X-bit indicator for the strongest coefficient index (i*,            f*), where X=┌log₂ K_(NZ)┐ or ┌log₂ 2L┐.            -   i. Strongest coefficient c_(l,i*,f*)=1 (hence its                amplitude/phase are not reported)        -   Two antenna polarization-specific reference amplitudes is            used.            -   i. For the polarization associated with the strongest                coefficient c_(l,i*,f*)=1, since the reference amplitude                p_(l,i,f) ⁽¹⁾=1, it is not reported            -   ii. For the other polarization, reference amplitude                p_(l,i,f) ⁽²⁾ is quantized to 4 bits.                -   1. The 4-bit amplitude alphabet is

$\left\{ {1,\left( \frac{1}{2} \right)^{\frac{1}{4}},\left( \frac{1}{4} \right)^{\frac{1}{4}},\left( \frac{1}{8} \right)^{\frac{1}{4}},\ldots,\left( \frac{1}{2^{14}} \right)^{\frac{1}{4}}} \right\}.$

-   -   -   For {c_(l,i,f), (i,f)≠(i*, f*)}:            -   i. For each polarization, differential amplitudes                p_(l,i,f) ⁽²⁾ of the coefficients calculated relative to                the associated polarization-specific reference amplitude                and quantized to 3 bits.            -   1. The 3-bit amplitude alphabet is

$\left\{ {1,\frac{1}{\sqrt{2}},\frac{1}{2},\frac{1}{2\sqrt{2}},\frac{1}{4},\frac{1}{4\sqrt{2}},\frac{1}{8},\frac{1}{8\sqrt{2}}} \right\}.$

-   -   -   -   2. Note: The final quantized amplitude p_(l,i,f) is                given by p_(l,i,f) ⁽¹⁾×p_(l,i,f) ⁽²⁾

        -   ii. Each phase is quantized to either 8PSK (N_(ph)=8) or            16PSK (N_(ph)=16) (which is configurable).

For the polarization r*∈{0,1} associated with the strongest coefficientc_(l,i*,f*), we have

$r^{*} = \left\lfloor \frac{i^{*}}{L} \right\rfloor$

and the reference amplitude p_(l,i,f) ⁽¹⁾=p_(l,r) ⁽¹⁾=1. For the otherpolarization r∈{0,1} and r≠r*, we have

$r = {\left( {\left\lfloor \frac{i^{*}}{L} \right\rfloor + 1} \right){mod}2}$

and the reference amplitude p_(l,i,f) ⁽¹⁾=p_(l,r) ⁽¹⁾ is quantized(reported) using the 4-bit amplitude codebook mentioned above.

In Rel. 16 enhanced Type II and Type II port selection codebooks, a UEcan be configured to report M FD basis vectors. In one example,

${M = \left\lceil {p \times \frac{N_{3}}{R}} \right\rceil},$

where R is higher-layer configured from {1,2} and p is higher-layerconfigured from {¼,½}. In one example, the p value is higher-layerconfigured for rank 1-2 CSI reporting. For rank>2 (e.g., rank 3-4), thep value (denoted by v₀) can be different. In one example, for rank 1-4,(p, v₀) is jointly configured from

$\left\{ {\left( {\frac{1}{2},\frac{1}{4}} \right),\left( {\frac{1}{4},\frac{1}{4}} \right),\left( {\frac{1}{4},\frac{1}{8}} \right)} \right\},{i.e.},{M = \left\lceil {p \times \frac{N_{3}}{R}} \right\rceil}$

for rank 1-2 and

$M = \left\lceil {v_{0} \times \frac{N_{3}}{R}} \right\rceil$

for rank 3-4. In one example, N₃=N_(SB)×R where N_(SB) is the number ofSBs for CQI reporting. In one example, M is replaced with M_(υ) to showits dependence on the rank value υ, hence p is replaced withp_(υ),υ∈{1,2} and v₀ is replaced with p_(υ),υ∈{3,4}.

A UE can be configured to report M_(υ) FD basis vectors in one-step fromN₃ basis vectors freely (independently) for each layer l∈{1, . . . , υ}of a rank υ CSI reporting. Alternatively, a UE can be configured toreport M_(υ) FD basis vectors in two-step as follows.

-   -   In step 1, an intermediate set (InS) comprising M₃′<N₃ basis        vectors is selected/reported, wherein the InS is common for all        layers.    -   In step 2, for each layer l∈{1, . . . , υ} of a rank υ CSI        reporting, M_(υ) FD basis vectors are selected/reported freely        (independently) from N₃′ basis vectors in the InS.

In one example, one-step method is used when N₃≤19 and two-step methodis used when N₃>19. In one example, N₃′=┌αM_(υ)┐ where α>1 is eitherfixed (to 2 for example) or configurable.

The codebook parameters used in the DFT based frequency domaincompression (Eq. 5) are (L, p_(υ) for υ∈{1,2}, p_(υ) for ν∈{3,4}, β, α,N_(ph)). The set of values for these codebook parameters are as follows.

-   -   L: the set of values is {2,4} in general, except L∈{2,4,6} for        rank 1-2, 32 CSI-RS antenna ports, and R=1.    -   (p_(υ) for υ∈{1,2}, p_(υ) for υ∈{(½,¼),(¼,¼),(¼,⅛)}    -   β∈{½,½,¾}.    -   α=2    -   N_(ph)=16.        The set of values for these codebook parameters are as in Table        1.

TABLE 1 p_(υ) paramCombination L υ ∈ {1, 2} υ ∈ {3, 4} β 1 2 ¼ ⅛ ¼ 2 2 ¼⅛ ½ 3 4 ¼ ⅛ ¼ 4 4 ¼ ⅛ ½ 5 4 ¼ ¼ ¾ 6 4 ½ ¼ ½ 7 6 ¼ — ½ 8 6 ¼ — ¾

In Rel. 17 (further enhanced Type II port selecting codebook),

${M \in \left\{ {1,2} \right\}},{L = {{\frac{K_{1}}{2}{where}{}K_{1}} = {\alpha \times P_{CSIRS}}}},$

and codebook parameters (M,α,β) are configured from Table 2.

TABLE 2 paramCombination-r17 M α β 1 1 ¾ ½ 2 1 1 ½ 3 1 1 ¾ 4 1 1 1 5 2 ½½ 6 2 ¾ ½ 7 2 1 ½ 8 2 1 ¾

The above-mentioned framework (Eq. 5) represents the precoding-matricesfor multiple (N₃) FD units using a linear combination (double sum) over2L (or K₁) SD beams/ports and M_(υ) FD beams. This framework can also beused to represent the precoding-matrices in time domain (TD) byreplacing the FD basis matrix W_(f) with a TD basis matrix W_(t),wherein the columns of W_(t) comprises M_(υ) TD beams that representsome form of delays or channel tap locations. Hence, a precoder W^(l)can be described as follows.

W=A _(l) C _(l) B _(l) ^(H) =W ₁ {tilde over (W)} ₂ W _(t) ^(H),  (Eq.5A)

In one example, the M_(υ) TD beams (representing delays or channel taplocations) are selected from a set of N₃ TD beams, i.e., N₃ correspondsto the maximum number of TD units, where each TD unit corresponds to adelay or channel tap location. In one example, a TD beam corresponds toa single delay or channel tap location. In another example, a TD beamcorresponds to multiple delays or channel tap locations. In anotherexample, a TD beam corresponds to a combination of multiple delays orchannel tap locations.

In one example, the codebook for the CSI report is according to at leastone of the following examples.

-   -   In one example, the codebook can be a Rel. 15 Type I        single-panel codebook (cf. 5.2.2.2.1, TS 38.214).    -   In one example, the codebook can be a Rel. 15 Type I multi-panel        codebook (cf. 5.2.2.2.2, TS 38.214).    -   In one example, the codebook can be a Rel. 15 Type II codebook        (cf. 5.2.2.2.3, TS 38.214).    -   In one example, the codebook can be a Rel. 15 port selection        Type II codebook (cf. 5.2.2.2.4, TS 38.214).    -   In one example, the codebook can be a Rel. 16 enhanced Type II        codebook (cf. 5.2.2.2.5, TS 38.214).    -   In one example, the codebook can be a Rel. 16 enhanced port        selection Type II codebook (cf. 5.2.2.2.6, TS 38.214).    -   In one example, the codebook can be a Rel. 17 further enhanced        port selection Type II codebook (cf. 5.2.2.2.7, TS 38.214).    -   In one example, the codebook is a new codebook for C-JT CSI        reporting.        -   In one example, the new codebook is a decoupled codebook            comprising the following components:            -   Intra-TRP: per TRP Rel. 16/17 Type II codebook                components, i.e., SD basis vectors (W1), FD basis                vectors (Wf), W2 components (e.g., SCI, indices of NZ                coefficients, and amplitude/phase of NZ coefficients).            -   Inter-TRP: co-amplitude and co-phase for each TRP.        -   In one example, the new codebook is a joint codebook            comprising following components:            -   Per TRP SD basis vectors (W1),            -   Single joint FD basis vectors (Wf), and            -   Single joint W2 components (e.g., SCI, indices of NZ                coefficients, and amplitude/phase of NZ coefficients).

FIG. 9 illustrates two new codebooks 900 according to embodiments of thepresent disclosure. The embodiment of the two new codebooks 900illustrated in FIG. 9 is for illustration only. FIG. 9 does not limitthe scope of this disclosure to any particular implementation of the twonew codebooks 900.

In one example, when the codebook is a legacy codebook (e.g., one ofRel. 15/16/17 NR codebooks, according to one of the examples above),then the CSI reporting is based on a CSI resource set comprising one ormultiple NZP CSI-RS resource(s), where each NZP CSI-RS resourcecomprises CSI-RS antenna ports for all TRPs/RRHs, i.e., P=Σ_(r=1)^(N)P_(r), where P is the total number of antenna ports, and P_(r) isthe number of antenna ports associated with r-th TRP. In this case, aTRP corresponds to (or maps to or is associated with) a group of antennaports.

In one example, when the codebook is a new codebook (e.g., one of thetwo new codebooks above), then the CSI reporting is based on a CSIresource set comprising one or multiple NZP CSI-RS resource(s).

-   -   In one example, each NZP CSI-RS resource comprises CSI-RS        antenna ports for all TRPs/RRHs. i.e., P=Σ_(r=1) ^(N)P_(r),        where P is the total number of antenna ports, and P_(r) is the        number of antenna ports associated with r-th TRP. In this case,        a TRP corresponds to (or maps to or is associated with) a group        of antenna ports.    -   In one example, each NZP CSI-RS resource corresponds to (or maps        to or is associated with) a TRP/RRH.

In one embodiment, a UE is configured with a CSI report (e.g., viahigher layer CSI-ReportConfig) based on a codebook for C-JT transmissionfrom multiple TRPs, as described in this disclosure, where the codebookparameters (such as α or L, β, p_(υ) or M_(υ)) are configured via ahigher-layer parameter ‘paramCombination-r18’.

-   -   In one example, the Rel. 16 parameter combination table for        ‘paraCombination-r16’ is reused for ‘paramCombination-r18’ (cf.        Table 1).    -   In one example, the Rel. 17 parameter combination table for        ‘paraCombination-r17’ is reused for ‘paramCombination-r18’ (cf.        Table 2).    -   In one example, a new table of parameter combination is used for        ‘paramCombination-r18’.    -   In one example, a table including existing Rel. 16 or Rel. 17        parameter combination(s) and new parameter combination(s) is        used for ‘paramCombination-r18’.

In one embodiment, L value configured for TRPs depends on the number ofTRPs (N_(TRP)).

In one example, L is the same for all TRPs (i.e., TRP-common), and itdepends on the number of TRPs (i.e., it can change depending on thevalue of N_(TRP)). For example,

-   -   L=2, 4, or 6 for 1 TRP (N_(TRP)=1),    -   L=2, 3 for 2 TRPs (N_(TRP)=2),    -   L=1, 2 for 3 TRPs (N_(TRP)=3), and    -   L=1, 2 for 4 TRPs (N_(TRP)=4).

In one example, the Rel.16 table of ‘paraCombination-r16’ is used (ornot used), and the L value depends on the number of TRPs (N_(TRP)), forexample, L for 1 TRP,

$\left\lceil \frac{L}{2} \right\rceil\left( {{{or}L} - 1} \right)$

for 2 TRPs,

$\left\lceil \frac{L}{3} \right\rceil\left( {{{or}L} - 2} \right)$

for 3 TRPs, and

$\left\lceil \frac{L}{4} \right\rceil\left( {{{or}L} - 4} \right)$

for 4 TRPs, where L is the configured value. For example, for the caseof 4 TRPs, if L=4 is indicated using the table of ‘paraCombination-r16’,the actual L value for each TRP is

$\left\lceil \frac{L}{4} \right\rceil = {1.}$

In another example, the Rel. 16 table of ‘paraCombination-r16’ is used(or not used), and the L value depends on the number of TRPs in apair-wise manner, for example, L for

${N_{TRP} = 1},2,{{{and}\left\lceil \frac{L}{2} \right\rceil{for}N_{TRP}} = 3},{4.}$

In another example, the Rel. 16 table of ‘paraCombination-r16’ is used(or not used), and the L value depends on the number of TRPs, forexample, L for

${N_{TRP} = 1},{{\left\lceil \frac{L}{2} \right\rceil{for}N_{TRP}} = 2},{{\left\lceil \frac{L}{4} \right\rceil{for}N_{TRP}} = 3},4.$

In one example, L can be different for some or all TRPs.

In one example, the configured L value is applied to a strongest TRP,and L−x (or ┌L/y┐) value is applied to the other remaining TRPs, where xor y can be fixed (e.g., x=1, y=2) or configured, or reported by the UE.

In one example, the configured L value is applied to two strongest TRPs,and L−x (or ┌L/y┐) value is applied to the other remaining TRPs, where xor y can be fixed (e.g., x=1, y=2) or configured, or reported by the UE.

In another example, L_(sum)≥ΣL_(n) is configured, where L_(n) is L valuefor TRP n. Under the constraint with the configured value of L_(sum),the UE (freely) selects L_(n) for TRP n. In this example, L_(sum) can beconfigured using a similar table (or the same table) of‘paraCombination-r16’, e.g., replacing L by L_(sum). In one example,L_(sum)=sL where L is the configured value and s is fixed (e.g., 2) orconfigured. In one example, L_(sum)≥N_(TRP). In one example, L_(n)≥1. Inone example, L_(n)≥0.

In another example, L_(n) is configured for each TRP n. In one example,L_(n) is indicated using the table of ‘paraCombination-r16’. In anotherexample, L_(n) is indicated using a new table of ‘paraCombination-r18’.

In another example, L₁ is configured for a first group of TRPs, and L₂is configured for a second group of TRPs. In one example, L₁ and L₂ areindicated using the table of ‘paraCombination-r16’. In one example, L₁and L₂ are indicated using a new table of ‘paraCombination-r18’. Inanother example, a constraint of L₂≤L₁ should satisfy whenselecting/indicating L₂.

In one example, L can be different for some or all TRPs, and it dependson the number of TRPs.

In one example, L_(sum)≥ΣL_(n) depends on the number of TRPs. Forexample,

-   -   L_(sum)=2,4,6 for 1 TRP    -   L_(sum)=2,4,6,8 for 2 TRPs    -   L_(sum)=3,4,6,9 for 3 TRPs    -   L_(sum)=4,6,8,12 for 4 TRPs

Under the constraint with the configured value of L_(sum), the UE(freely) selects L_(n) for TRP n. In this example, L_(sum) can beconfigured using a similar table (or the same table) of‘paraCombination-r16’, e.g., replacing L by L_(sum).

In one example, a pair of (L, N_(TRP)) can be configured. For example,gNB or NW can indicate one pair among (2,2), (3,2), (4,2), (1,3), (2,3),(3,3), (1,4), and (2,4).

In one example, the UE determines L value for TRPs, e.g., L for strongTRPs, and

$\left\lceil \frac{L}{2} \right\rceil$

for weak TRPs, and the UE reports strong/weak TRP indices.

In one example, α is the same for all TRPs (i.e., TRP-common), and itdepends on the number of TRPs (i.e., it can change depending on thevalue of N_(TRP)). For example,

${{\bullet \alpha} = \frac{1}{2}},{\frac{3}{4}{or}1{for}{}1{{TRP}\left( {N_{TRP} = 1} \right)}},$${{\bullet \alpha} = \frac{1}{4}},{\frac{1}{2}{for}3/4{{TRPs}\left( {N_{TRP} = 2} \right)}},$${{\bullet \alpha} = \frac{1}{4}},{\frac{1}{2}{for}3{{TRPs}\left( {N_{TRP} = 3} \right)}},{and}$${{\bullet \alpha} = \frac{1}{4}},{\frac{1}{2}{for}4{{{TRPs}\left( {N_{TRP} = 4} \right)}.}}$

In one example, the Rel.17 table of ‘paraCombination-r17’ is used (ornot used), and the α value depends on the number of TRPs (N_(TRP)), forexample, α for 1 TRP,

$\frac{\alpha}{2}$

for 2 TRPs,

$\frac{\alpha}{3}$

for 3 TRPs, and

$\frac{\alpha}{4}$

for 4 TRPs, where α is the configured value. For example, for the caseof 4 TRPs, if α=1 is indicated using the table of ‘paraCombination-r17’,the actual α value for each TRP is

$\frac{\alpha}{4}.$

In another example, the Rel. 17 table of ‘paraCombination-r17’ is used(or not used), and the α value depends on the number of TRPs in apair-wise manner, for example, α for

${N_{TRP} = 1},2,{{{and}\frac{\alpha}{2}N_{TRP}} = 3},{4.}$

In another example, the Rel. 17 table of ‘paraCombination-r17’ is used(or not used), and the α value depends on the number of TRPs, forexample,

${{\alpha{for}N_{TRP}} = 1},{{\frac{\alpha}{2}{for}N_{TRP}} = 2},{{\frac{\alpha}{4}N_{TRP}} = 3},4.$

In one example, α can be different for some or all TRPs.

In one example, the configured a value is applied to a strongest TRP,and α/y value is applied to the other remaining TRPs, where y can befixed (e.g., y=2) or configured, or reported by the UE.

In one example, the configured a value is applied to two strongest TRPs,and α/y value is applied to the other remaining TRPs, where y can befixed (e.g., y=2) or configured, or reported by the UE.

In another example, α_(sum)≥Σα_(n) is configured, where α_(n) is α valuefor TRP n. Under the constraint with the configured value of α_(sum),the UE (freely) selects L_(n) corresponding to an for TRP n. In thisexample, α_(sum) can be configured using a similar table (or the sametable) of ‘paraCombination-r17’, e.g., replacing a by α_(sum). In oneexample, α_(sum)=sα where α is the configured value and s is fixed(e.g., 2) or configured. In one example, L_(sum) corresponding toα_(sum) is less than or equal to N_(TRP). In one example, L_(n)corresponding to α_(n) is less than or equal to 1. In one example, L_(n)corresponding to α_(n) is less than or equal to 0.

In another example, an is configured for each TRP n. In one example,α_(n) is indicated using the Rel-17 table of ‘paraCombination-r17’. Inanother example, α_(n) is indicated using a new table of‘paraCombination-r18’.

In another example, α₁ is configured for a first group of TRPs, and α₂is configured for a second group of TRPs. In one example, α₁ and α₂ areindicated using the table of ‘paraCombination-r17’. In one example, α₁and α₂ are indicated using a new table of paraCombination-r18′. Inanother example, a constraint of α₂≤α₁ should satisfy whenselecting/indicating α₂.

In one example, α can be different for some or all TRPs, and it dependson the number of TRPs.

In one example, α_(sum)≥ΣL_(n), depends on the number of TRPs. Forexample,

${\alpha_{sum} = \frac{1}{2}},\frac{3}{4},{1{for}1{TRP}},$${\alpha_{sum} = \frac{3}{4}},1,\frac{3}{2},{2{for}2{TRPs}},$${\alpha_{sum} = 1},\frac{3}{2},2,{\frac{5}{2}{for}3{TRPs}},{and}$${\alpha_{sum} = 1},\frac{3}{2},2,{3{for}4{{TRPs}.}}$

Under the constraint with the configured value of α_(sum) the UE(freely) selects L_(n) corresponding to α_(n) for TRP n. In thisexample, α_(sum) can be configured using a similar table (or the sametable) of ‘paraCombination-r17’, e.g., replacing a by α_(sum).

In one example, a pair of (α, N_(TRP)) can be configured. For example,gNB or NW can indicate one pair among (1/2,2), (3/4,2), (1,2), (1/4,3),(1/2,3), (1,3), (1/4,4), and (1/2,4).

In one example, the UE determines a value for TRPs, e.g., α for strongTRPs, and

$\frac{\alpha}{2}$

for weak TRPs, and the UE reports strong/weak TRP indices.

In embodiment, M value for TRPs depends on the number of TRPs (N_(TRP)).p can be configured to indicate M similar to Rel-16, e.g.,

$M = {\left\lceil {p \times \frac{N_{3}}{R}} \right\rceil.}$

M can directly be configured without p value. p value can berank-dependent (similar to Rel-16). M value is rank-dependent similar toRel-16, that is

$M_{v} = {\left\lceil {p_{v} \times \frac{N_{3}}{R}} \right\rceil.}$

We drop v index when it is not needed.

In one example, p is the same for all TRPs (i.e., TRP-common), and itdepends on the number of TRPs (i.e., it can change depending on thevalue of N_(TRP)). For example,

${p = \frac{1}{8}},\frac{1}{4},{{or}\frac{1}{2}{for}1{TRP}{\left( {N_{TRP} = 1} \right).}}$${p = \frac{1}{8}},\frac{1}{4},{{or}\frac{1}{2}{for}2{TRPs}\left( {N_{TRP} = 2} \right)},$${p = \frac{1}{16}},\frac{1}{8},{\frac{1}{4}{for}3{TRPs}\left( {N_{TRP} = 3} \right)},{and}$${p = \frac{1}{16}},\frac{1}{8},{\frac{1}{4}{for}4{TRPs}{\left( {N_{TRP} = 4} \right).}}$

In one example, the Rel-16 table of ‘paraCombination-r16’ is used (ornot used), and the p value depends on the number of TRPs, for example, pfor 1 TRP,

$\frac{p}{2}$

for 2 TRPs,

$\frac{p}{3}$

for 3 TRPs, and

$\frac{p}{4}$

for 4 TRPs, where p is the configured value. For example, for the caseof 4 TRPs, if

$p = \frac{1}{2}$

is indicated using the table of ‘paraCombination-r16’, the actual pvalue for each TRP is

$\frac{p}{4}.$

In another example, the Rel-16 table of ‘paraCombination-r16’ is used(or not used), and the p value depends on the number of TRPs in apair-wise manner, for example, p for

${N_{TRP} = 1},2,{{{and}\frac{p}{2}N_{TRP}} = 3},{4.}$

In another example, the Rel-16 table of ‘paraCombination-r16’ is used(or not used), and the p value depends on the number of TRPs, forexample, p for

${N_{TRP} = 1},{{\frac{p}{2}{for}N_{TRP}} = 2},{{\frac{p}{4}{for}N_{TRP}} = {3,4.}}$

In one example, p can be different for some or all TRPs.

In one example, p value is applied to a strongest TRP, and p/y value isapplied to the other remaining TRPs, where e.g., y can be fixed to 2 or3, or configured, or reported by the UE.

In one example, p value is applied to two strongest TRPs, and p/y valueis applied to the other remaining TRPs, where e.g., y can be fixed to 2or 3, or configured, or reported by the UE.

In another example, let M_(sum)≥ΣM_(n) and p_(sum) is configured toindicate

${M_{sum} \geq \left\lceil {p_{sum} \times \frac{N_{3}}{R}} \right\rceil},$

where M_(n) is M value for TRP n. Under the constraint with theconfigured value of M_(sum), the UE (freely) selects M_(n) for TRP n. Inthis example, p_(sum) can be configured using a similar table (or thesame table) of ‘paraCombination-r16’, e.g., replacing p by p_(sum). Inone example, M_(sum)=SM where M is the configured value and s is fixed(e.g., 2) or configured. In one example, M_(sum)≥N_(TRP). In oneexample, M_(n)≥1. In one example, M_(n)≥0.

In another example, p₁, is configured for each TRP n. In one example,p_(n) is indicated using the table of ‘paraCombination-r16’. In anotherexample, p_(n) is indicated using a new table of ‘paraCombination-r18’.

In another example, p₁ is configured for a first group of TRPs, and p₂is configured for a second group of TRPs. In one example, p₁ and p₂ areindicated using the table of ‘paraCombination-r16’. In one example, p₁and p₂ are indicated using a new table of ‘paraCombination-r18’. Inanother example, a constraint of p₂≤p₁ should satisfy whenselecting/indicating p₂.

In one example, M can be different for some or all TRPs, and it dependson the number of TRPs.

In one example, M_(sum)≥ΣM_(n) depends on the number of TRPs, andp_(sum) is configured to indicate

$M_{sum} \geq {\left\lceil {p_{sum} \times \frac{N_{3}}{R}} \right\rceil.}$

For example,

${p_{sum} = \frac{1}{8}},\frac{1}{4},{{or}\frac{1}{2}{for}1{TRP}},$${p_{sum} = \frac{1}{8}},\frac{1}{4},{{or}\frac{1}{2}{for}2{TRPs}},$${p_{sum} = \frac{1}{16}},\frac{1}{8},{\frac{1}{4}{for}3{TRPs}},{and}$${p_{sum} = \frac{1}{16}},\frac{1}{8},{\frac{1}{4}{for}4{{TRPs}.}}$

Under the constraint with the configured value of p_(sum) (i.e.,M_(sum)), the UE (freely) selects M_(n) for TRP n. In this example,p_(sum) can be configured using a similar table (or the same table) of‘paraCombination-r16’, e.g., replacing p by p_(sum).

In one example, p_(sum) can be rank-dependent similar to Rel-16 forp_(v).

In one example, a pair of (p, N_(TRP)) can be configured. For example,gNB or NW can indicate one pair among (½,2), (¼,2), (⅛,2), (¼,3), (⅛,3),( 1/16,3), (⅛,4), and ( 1/16,4).

In one example, the UE determines M value for TRPs, e.g., M for strongTRPs, and

$\left\lceil \frac{M}{2} \right\rceil$

for weak and the UE reports strong/weak TRP indices.

In one example, M is the same for all TRPs (i.e., TRP-common), and itdepends on the number of TRPs (i.e., it can change depending on thevalue of N_(TRP)). For example,

-   -   M=1, 2 for 1 TRP (N_(TRP)=1),    -   M=1, 2, or 3 for 2 TRPs (N_(TRP)=2),    -   M=2, 3, 4 for 3 TRPs (N_(TRP)=3), and    -   M=3, 4 for 4 TRPs (N_(TRP)=4).

In one example, the Rel-17 table of ‘paraCombination-r17’ is used (ornot used), and the M value depends on the number of TRPs, for example, Mfor 1 TRP,

${\left\lceil \frac{M}{2} \right\rceil\left( {{{or}M} - 1} \right){for}2{TRPs}},{\left\lceil \frac{M}{3} \right\rceil\left( {{{or}M} - 2} \right){for}3{TRPs}},{and}$$\left\lceil \frac{M}{4} \right\rceil\left( {{{or}M} - 3} \right)$

for 4 TRPs, where M is the configured value. For example, for the caseof 4 TRPs, if M=2 is indicated using the table of ‘paraCombination-r16’,the actual M value for each TRP is

$\left\lceil \frac{M}{4} \right\rceil = {1.}$

In another example, the Rel-17 table of ‘paraCombination-r17’ is used(or not used), and the M value depends on the number of TRPs in apair-wise manner, for example, M for

${N_{TRP} = {1,2}},{{{and}\left\lceil \frac{M}{2} \right\rceil{for}N_{TRP}} = {3,4.}}$

In another example, the Rel-17 table of ‘paraCombination-r17’ is used(or not used), and the p value depends on the number of TRPs, forexample, M for

${N_{TRP} = 1},{{\left\lceil \frac{M}{2} \right\rceil{for}N_{TRP}} = 2},{{\left\lceil \frac{M}{4} \right\rceil{for}N_{TRP}} = {3,4.}}$

In one example, M can be different for some or all TRPs.

In one example, M value is applied to a strongest TRP, and ┌M/y┐ valueis applied to the other remaining TRPs, where e.g., y can be fixed to 2or 3, or configured, or reported by the UE.

In one example, p value is applied to two strongest TRPs, and ┌M/y┐value is applied to the other remaining TRPs, where e.g., y can be fixedto 2 or 3, or configured, or reported by the UE.

In another example, M_(sum)≥ΣM_(n) is configured, where M_(n) is M valuefor TRP n. Under the constraint with the configured value of M_(sum),the UE (freely) selects M_(n) for TRP n. In this example, M_(sum) can beconfigured using a similar table (or the same table) ofparaCombination-r17′, e.g., replacing p by p_(sum). In one example,M_(sum)=SM where M is the configured value and s is fixed (e.g., 2) orconfigured. In one example, M_(sum)≥N_(TRP). In one example, M_(n)≥1. Inone example, M_(n)≥0.

In another example, M_(n) is configured for each TRP n. In one example,M_(n) is indicated using the table (or a similar table) of ‘paraCombination-r17’. In another example, M_(n) is indicated using a newtable of ‘paraCombination-r18’.

In another example, M₁ is configured for a first group of TRPs, and M₂is configured for a second group of TRPs. In one example, M₁ and M₂ areindicated using the table (or a similar table) of ‘paraCombination-r17’.In one example, M₁ and M₂ are indicated using a new table of‘paraCombination-r18’. In another example, a constraint of M₂≤M₁ shouldsatisfy when selecting/indicating M₂.

In one example, M can be different for some or all TRPs, and it dependson the number of TRPs.

In one example, M_(sum)≥ΣM_(n) depends on the number of TRPs, Forexample,

-   -   M_(sum)=1 or 2 for 1 TRP,    -   M_(sum)=2 or 3 for 2 TRPs,    -   M_(sum)=2,3,4 for 3 TRPs, and    -   M_(sum)=3,4,5 for 4 TRPs.

Under the constraint with the configured value of M_(sum), the UE(freely) selects M_(n) for TRP n. In this example, M_(sum) can beconfigured using a similar table (or the same table) of ‘paraCombination-r17’, e.g., replacing M by M_(sum).

In one example, M_(sum) can be rank-dependent similar to Rel-16 forp_(v).

In one example, a pair of (M, N_(TRP)) can be configured. For example,gNB or NW can indicate one pair among (1,2), (2,2), (3,2), (1,3), (2,3),(3,3), (1,4), and (2,4).

In one embodiment, L, M values for TRPs depend on the number of TRPs(N_(TRP)). Any combination of L (or α) in certain embodiments herein andM (or p) in certain embodiments herein can be applicable to thisembodiment.

In one embodiment, (L,p) value configured for TRPs depends on the numberof TRPs (N_(TRP)).

In one example, (L,p) is the same for all TRPs (i.e., TRP-common), andit depends on the number of TRPs (i.e., it can change depending on thevalue of N_(TRP)).

In one example, the Rel.16 table of ‘ paraCombination-r16’ is used (ornot used), and the L and p values depend on the number of TRPs(N_(TRP)), for example, L for 1 TRP,

${\left\lceil \frac{L}{2} \right\rceil\left( {{{or}L} - 1} \right){and}\frac{p}{2}{for}2{TRPs}},$${\left\lceil \frac{L}{3} \right\rceil\left( {{{or}L} - 2} \right){and}\frac{p}{3}{for}3{TRPs}},{and}$${\left\lceil \frac{L}{4} \right\rceil\left( {{{or}L} - 4} \right){and}\frac{p}{4}{for}4{TRPs}},$

where L is the configured value. For example, for the case of 4 TRPs, ifL=4, p=1/2 is indicated using the table of ‘ paraCombination-r16’, theactual L value for each TRP is

$\left\lceil \frac{L}{4} \right\rceil = {{1{and}\frac{p}{4}} = {\frac{1}{8}.}}$

In another example, the Rel. 16 table of ‘paraCombination-r16’ is used(or not used), and the L and p values depend on the number of TRPs in apair-wise manner, for example, L and p for

${N_{TRP} = {1,2}},{{{and}\left\lceil \frac{L}{2} \right\rceil{and}\frac{p}{2}{for}N_{TRP}} = {3,4.}}$

In another example, the Rel. 16 table of ‘paraCombination-r16’ is used(or not used), and the L and p values depend on the number of TRPs, forexample, L and p for

${N_{TRP} = 1},{{\left\lceil \frac{L}{2} \right\rceil{and}\frac{p}{2}{for}N_{TRP}} = 2},$${\left\lceil \frac{L}{4} \right\rceil{and}\frac{p}{4}{for}N_{TRP}} = {3,4.}$

In one example, L and p can be different for some or all TRPs.

In one example, the configured L and p values are applied to a strongestTRP, and L−x (or ┌L/y┐) and p/y₂ values are applied to the otherremaining TRPs, where x or y and y₂ can be fixed (e.g., x=1, y=2, y₂=2)or configured, or reported by the UE. In one example, y=y₂.

In one example, the configured L and p values are applied to twostrongest TRPs, L−x (or ┌L/y┐) and p/y₂ values are applied to the otherremaining TRPs, where x or y and y₂ can be fixed (e.g., x=1, y=2, y₂=2)or configured, or reported by the UE. In one example, y=y₂.

In another example, L_(sum)≥ΣL_(n), and p_(sum)≥Σp_(n), are configured,where L_(n) is L value for TRP n and p_(n) is p value for TRP n. Underthe constraint with the configured values of L_(sum), and p_(sum) the UE(freely) selects L_(n) and M_(n) (corresponding to p_(n)) for TRP n. Inthis example, L_(sum) and Nun., can be configured using a similar table(or the same table) of ‘paraCombination-r16’, e.g., replacing L byL_(sum) and p by p_(sum), respectively. In one example, L_(sum)=sL whereL is the configured value and s is fixed (e.g., 2) or configured. In oneexample, L_(sum)≥N_(trp). In one example, L_(n)≥1. In one example,L_(n)≥0. In one example, M_(sum)=s₂M where M is the configured value ands₂ is fixed (e.g., 2) or configured. In one example, M_(sum)≥N_(TRP). Inone example, M_(n)≥1. In one example, M_(n)≥0. In one example, s=s₂.

In another example, L_(n) and p_(n) are configured for each TRP n. Inone example, L_(n) and p_(n) are indicated using the table of‘paraCombination-r16’. In another example, L_(n) and p_(n) are indicatedusing a new table of ‘paraCombination-r18’.

In another example, L₁ and p₁ are configured for a first group of TRPs,and L₂ and p₂ configured for a second group of TRPs. In one example, L₁and L₂, and p₁ and p₂ are indicated using the table of‘paraCombination-r16’. In one example, L₁ and L₂ and p₁ and p₂ areindicated using a new table of ‘paraCombination-r18’. In anotherexample, a constraint of L₂≤L₁ should satisfy when selecting/indicatingL₂. In another example, a constraint of p₂≤p₁ should satisfy whenselecting/indicating p₂.

In one example, L and p can be different for some or all TRPs, and itdepends on the number of TRPs.

In one example, L_(sum)≥ΣL_(n) and p_(sum)≥Σp_(n) depend on the numberof TRPs.

Under the constraint with the configured values of L_(sum) and p_(sum),the UE (freely) selects L_(n) and p_(n) for TRP n. In this example,L_(sum) and p_(sum) can be configured using a similar table (or the sametable) of ‘paraCombination-r16’, e.g., replacing L by L_(sum), and p byp_(sum), respectively.

In one example, a tuple of (L, p, N_(TRP)) can be configured. Forexample, gNB or NW can indicate one tuple among (2,1/4, 2), (3,1/4,2),(4,1/8,2), (1,1/4,3), (2,1/8,3), (3,1/8,3), (1,1/8,4), and (2,1/8,4).

In one example, the UE determines L and p values for TRPs, e.g., L and pfor strong TRPs, and

$\left\lceil \frac{L}{2} \right\rceil{and}\frac{p}{2}$

for weak TRPs, and the UE reports strong/weak TRP indices.

In one embodiment, a table of ‘paraCombination-r18’ is designed based onthe existing Rel. 16/17 table for ‘paraCombination-r16’ (Table 1) or‘paraCombination-r17’ (Table 2), and the UE can be configured using thetable for codebook parameters.

In one example, one value (C₁) from the table of ‘paraCombination-r16’or ‘paraCombination-r17’ is configured for a strongest TRP (or twostrongest TRPs), and another value (C₂) from the table of‘paraCombination-r16’ or ‘paraCombination-r17’ is configured for theremaining TRPs.

In one example, one value (C₁) from the table of ‘paraCombination-r16’or ‘paraCombination-r17’ is configured for a strongest TRP (or twostrongest TRPs), and another value (C₂) from the table of‘paraCombination-r16’ or ‘paraCombination-r17’ is fixed for theremaining TRPs, e.g., C₂=1.

In one example, one value (C₁) from the table of ‘paraCombination-r16’or ‘paraCombination-r17’ is configured for a strongest TRP (or twostrongest TRPs), and another value (C₂) from the table of‘paraCombination-r16’ or ‘paraCombination-r17’ is determined based on C₁for the remaining TRPs, in one example C₂<C₁. For example, C₂=C₁−1, ormax(1, C₁−1).

In one example, one value (C₁) from the table of ‘paraCombination-r16’or ‘paraCombination-r17’ is configured for a strongest TRP (or twostrongest TRPs), and another value (C₂) from the table of‘paraCombination-r16’ or ‘paraCombination-r17’ is configured with arestriction based on C₁ for the remaining TRPs, e.g., C₂≤C₁. Forexample, if C₁=4, then C₂ is selected from {1,2,3,4}.

The UE can report a strongest TRP index (or indices of 2 or a fewstrongest TRPs) in the relevant examples above or below.

In one example, Cn from the table of ‘paraCombination-r16’ or‘paraCombination-r17’ is configured for TRP n for n=1, . . . , N_(TRP).

In one example, some restriction on L can be applied to select Cn. Forexample, a total number of L beams across TRPs (i.e., L_(sum)) can beconstrained. For example, if L_(sum)=8 and N_(TRP)=3, (C₁, C₂,C₃)=(1,1,3) can be one possible value.

In one example, some restriction on M(or p) can be applied to select Cn.For example, a total number of M beams across TRPs (i.e., M_(sum) orp_(sum)) can be constrained.

In one example, some restriction on M (or p) and L can be applied toselect Cn. For example, a total number of M beams across TRPs (i.e.,M_(sum) or p_(sum)) and a total number of L beams (i.e., L_(sum)) can beconstrained.

In one example, a table of ‘paraCombination-r18’ is designed based on amixed version of the existing tables for ‘paraCombination-r16’ or‘paraCombination-r17’ and a new parameter-combination table, and the UEcan be configured using the table for codebook parameters.

In one example, the new table includes combinations with new L value(s).For example, the new L value(s) can include 1 or 3 (or 5). An example isdescribed in Table 3.

In one example,

$p_{v} = \frac{1}{2}$

is not included in the table.

Any table including at least one of the combinations provided in thetables in this disclosure can be an example for the table of‘paraCombination-r18’.

TABLE 3 p_(υ) paramCombination-r18 L υ ∈ {1, 2} υ ∈ {3, 4} β 1 2 ¼ ⅛ ¼ 22 ¼ ⅛ ½ 3 4 ¼ ⅛ ¼ 4 4 ¼ ⅛ ½ 5 4 ¼ ¼ ¾ 6 4 ½ ¼ ½ 7 6 ¼ — ½ 8 6 ¼ — ¾ 9 1¼ ⅛ ¼ 10 1 ¼ ⅛ ½ 11 1 ¼ ⅛ ¾ 12 1 ¼ ¼ ¼ 13 1 ¼ ¼ ½ 14 1 ¼ ¼ ¾ 15 1 ½ ¼ ¼16 1 ½ ¼ ½ 17 1 ½ ¼ ¾ 18 1 ¼ — ¼ 19 1 ¼ — ½ 20 1 ¼ — ¾ 21 3 ¼ ⅛ ¼ 22 3 ¼⅛ ½ 23 3 ¼ ⅛ ¾ 24 3 ¼ ¼ ¼ 25 3 ¼ ¼ ½ 26 3 ¼ ¼ ¾ 27 3 ½ ¼ ¼ 28 3 ½ ¼ ½ 293 ½ ¼ ¾ 30 3 ¼ — ¼ 31 3 ¼ — ½ 32 3 ¼ — ¾

In one example, the new table includes combinations with new a value(s).For example, the new a value(s) can include 1/4 or 1/8, or 1/16. Anexample is described in Table 4.

Any table including at least one of the combinations provided in thetables in this disclosure can be an example for the table of‘paraCombination-r18’.

TABLE 4 paramCombination-r18 M α β 1 1 ¾ ½ 2 1 1 ½ 3 1 1 ¾ 4 1 1 1 5 2 ½½ 6 2 ¾ ½ 7 2 1 ½ 8 2 1 ¾ 9 1 ½ ½ 10 1 ½ ¾ 11 1 ½ 1 12 1 ¼ ½ 13 1 ¼ ¾ 141 ¼ 1 15 2 ¼ ½ 16 2 ¼ ¾ 17 1 ⅛ ½ 18 1 ⅛ ¾ 19 1 ⅛ 1 20 2 ⅛ ½ 21 2 ⅛ ¾ 221 1/16 ½ 23 1 1/16 ¾ 24 1 1/16 1 25 2 1/16 ½ 26 2 1/16 ¾

In one example, the new table includes combinations with new p value(s).For example, the new p value(s) can include 1/6 or 1/10 or 1/16. Anexample is described in Table 5.

Any table including at least one of the combinations provided in thetables in this disclosure can be an example for the table of‘paraCombination-r18’.

TABLE 5 p_(υ) paramCombination-r18 L υ ∈ {1, 2} υ ∈ {3, 4} β 1 2 ¼ ⅛ ¼ 22 ¼ ⅛ ½ 3 4 ¼ ⅛ ¼ 4 4 ¼ ⅛ ½ 5 4 ¼ ¼ ¾ 6 4 ½ ¼ ½ 7 6 ¼ — ½ 8 6 ¼ — ¾ 9 2⅙ ⅛ ¼ 10 2 ⅙ ⅛ ½ 11 4 ⅙ ⅛ ¼ 12 4 ⅙ ⅛ ½ 13 4 ⅙ ⅙ ¾ 14 6 ⅙ — ½ 15 6 ⅙ — ¾16 2 ⅙ 1/10 ¼ 17 2 ⅙ 1/10 ½ 18 4 ⅙ 1/10 ¼ 19 4 ⅙ 1/10 ½ 20 2 ⅙ 1/16 ¼ 212 ⅙ 1/16 ½ 22 4 ⅙ 1/16 ¼ 23 4 ⅙ 1/16 ½ 24 2 ⅛ 1/10 ¼ 25 2 ⅛ 1/10 ½ 26 4⅛ 1/10 ¼ 27 4 ⅛ 1/10 ½ 28 4 ⅛ 1/10 ¾ 29 6 ⅛ — ½ 30 6 ⅛ — ¾ 31 2 ⅛ 1/16 ¼32 2 ⅛ 1/16 ½ 33 4 ⅛ 1/16 ¼ 33 4 ⅛ 1/16 ½ 34 4 ⅛ ⅛ ¾ 35 2 1/10 1/16 ¼ 362 1/10 1/16 ½ 37 4 1/10 1/16 ¼ 38 4 1/10 1/16 ½ 39 4 1/10 1/10 ¾ 40 61/10 — ½ 41 6 1/10 — ¾

In one example, the new table includes combinations with new L, pvalue(s). For example, the new L, p value(s) can include (1,1/8) or(1,1/6), (1,1/10), (1,1/16), (3,1/8), (3,1/6), (3,1/10), or (3,16). Anexample is described in Table 6.

Any table including at least one of the combinations provided in thetables in this disclosure can be an example for the table of‘paraCombination-r18’.

TABLE 6 p_(υ) paramCombination-r18 L υ ∈ {1, 2} υ ∈ {3, 4} β 1 2 ¼ ⅛ ¼ 22 ¼ ⅛ ½ 3 4 ¼ ⅛ ¼ 4 4 ¼ ⅛ ½ 5 4 ¼ ¼ ¾ 6 4 ½ ¼ ½ 7 6 ¼ — ½ 8 6 ¼ — ¾ 9 1⅙ ⅛ ¼ 10 1 ⅙ ⅛ ½ 11 1 ⅙ ⅛ ¾ 12 1 ⅙ ⅙ ¼ 13 1 ⅙ ⅙ ½ 14 1 ⅙ ⅙ ¾ 15 1 ⅙ — ¼16 1 ⅙ — ½ 17 1 ⅙ — ¾ 18 1 ⅙ 1/10 ¼ 19 1 ⅙ 1/10 ½ 20 1 ⅙ 1/10 ¾ 21 1 ⅙1/16 ¼ 22 1 ⅙ 1/16 ½ 23 1 ⅙ 1/16 ¾ 24 3 ⅙ ⅛ ¼ 25 3 ⅙ ⅛ ½ 26 3 ⅙ ⅛ ¾ 27 3⅙ ⅙ ¼ 28 3 ⅙ ⅙ ½ 29 3 ⅙ ⅙ ¾ 30 3 ⅙ — ¼ 31 3 ⅙ — ½ 32 3 ⅙ — ¾ 33 3 ⅙ 1/10¼ 34 3 ⅙ 1/10 ½ 35 3 ⅙ 1/10 ¾ 36 3 ⅙ 1/16 ¼ 37 3 ⅙ 1/16 ½ 38 3 ⅙ 1/16 ¾39 1 ⅛ ⅛ ¼ 40 1 ⅛ ⅛ ½ 41 1 ⅛ ⅛ ¾ 42 1 ⅛ — ¼ 43 1 ⅛ — ½ 44 1 ⅛ — ¾ 45 1 ⅛1/10 ¼ 46 1 ⅛ 1/10 ½ 47 1 ⅛ 1/10 ¾ 48 1 ⅛ 1/16 ¼ 49 1 ⅛ 1/16 ½ 50 1 ⅛1/16 ¾ 51 3 ⅛ ⅛ ¼ 52 3 ⅛ ⅛ ½ 53 3 ⅛ ⅛ ¾ 54 3 ⅛ — ¼ 55 3 ⅛ — ½ 56 3 ⅛ — ¾57 3 ⅛ 1/10 ¼ 58 3 ⅛ 1/10 ½ 59 3 ⅛ 1/10 ¾ 60 3 ⅛ 1/16 ¼ 61 3 ⅛ 1/16 ½ 623 ⅛ 1/16 ¾ 63 1 1/10 — ¼ 64 1 1/10 — ½ 65 1 1/10 — ¾ 66 1 1/10 1/10 ¼ 671 1/10 1/10 ½ 68 1 1/10 1/10 ¾ 69 1 1/10 1/16 ¼ 70 1 1/10 1/16 ½ 71 11/10 1/16 ¾ 72 3 1/10 — ¼ 73 3 1/10 — ½ 74 3 1/10 — ¾ 75 3 1/10 1/10 ¼76 3 1/10 1/10 ½ 77 3 1/10 1/10 ¾ 78 3 1/10 1/16 ¼ 79 3 1/10 1/16 ½ 80 31/10 1/16 ¾ 81 1 1/16 — ¼ 82 1 1/16 — ½ 83 1 1/16 — ¾ 84 1 1/16 1/16 ¼85 1 1/16 1/16 ½ 86 1 1/16 1/16 ¾ 87 3 1/16 — ¼ 88 3 1/16 — ½ 89 3 1/16— ¾ 90 3 1/16 1/16 ¼ 91 3 1/16 1/16 ½ 92 3 1/16 1/16 ¾

In one example, the new table includes new L (or a) and M (or p) values.

In one example, the new table includes L (or a) and values. In oneexample, new values of β such as, ⅕,⅙, 1/7,⅛, 1/9, 1/10, 1/11, 1/12,1/13, 1/14, 1/15, 1/16, . . . , 1/32,⅗, 3/7,⅜, 3/10, 3/11, 3/13, 3/14,3/16, 3/32, . . . , can be included in the table.

In one example, the new table includes M (or p) and values. In oneexample, new values of such as can ⅕,⅙, 1/7,⅛, 1/9, 1/10, 1/11, 1/12,1/13, 1/14, 1/15, 1/16, . . . , 1/32,⅗, 3/7,⅜, 3/10, 3/11, 3/13, 3/14,3/16, 3/32, . . . , can be included in the table.

In one example, the new table includes L (or α), M (or p), and β values.In one example, new values of β such as ⅕,⅙, 1/7,⅛, 1/9, 1/10, 1/11,1/12, 1/13, 1/14, 1/15, 1/16, . . . , 1/32,⅗, 3/7,⅜, 3/10, 3/11, 3/13,3/14, 3/16, 3/32, . . . , can be included in the table.

In one example, the new table includes ΔL (or Δα) values.

In one example, the new table includes ΔL (or Δα) and ΔM (or Δp) values.

In one example, the new table includes ΔL (or Δα) and Δβ values.

In one example, the new table includes ΔM (or Δp) and Δβ values.

In one example, the new table includes ΔL (or Δα), ΔM (or Δp), and Δβvalues.

Here, the ‘ΔX’ in the new table means a relationship from X valueselected/configured using the existing table. In one example, therelationship corresponds to subtraction (e.g., X₁−X₂=Δλ, where X₁ is avalue selected from the existing table, and X₂ is a value selected fromthe new table. Here, e.g., ΔX could be 0,1,2, . . . and so on). Inanother example, the relationship corresponds to division, (e.g.,X₂=┌ΔX×X₁┐, where X₁ is a value selected from the existing table, and X₂is a value selected from the new table. Here,

${{\Delta X} = \frac{1}{2}},\frac{1}{3},$

. . . and so on.)

In one example, the new table includes any combination of the aboveparameters. For example, the new table includes ΔL, ΔM, and β.

In one example, one value (C₁) from the table of ‘paraCombination-r16’(Table 1) or ‘paraCombination-r17’ (Table 2) is configured for astrongest TRP (or two strongest TRPs), and another value (C₂) from a newparameter-combination table (e.g., a table including at least one ofcombinations provided in Tables 3-6) is configured for the remainingTRPs.

In one example, one value (C₁) from the table of ‘paraCombination-r16’(Table 1) or ‘paraCombination-r17’ (Table 2) is configured for astrongest TRP (or two strongest TRPs), and another value (C₂) from a newparameter-combination table (e.g., a table including at least one ofcombinations provided in Tables 3-6) is (implicitly) determined based onC₁ for the remaining TRPs.

In one example, one value (C₁) from the table of ‘paraCombination-r16’(Table 1) or ‘paraCombination-r17’ (Table 2) is configured for astrongest TRP (or two strongest TRPs), and another value (C₂) from a newparameter-combination table (e.g., a table including at least one ofcombinations provided in Tables 3-6) is configured with a restrictionbased on C₁ for the remaining TRPs.

The UE can report a strongest TRP index (or indices of 2 or a fewstrongest TRPs) in the relevant examples above or below.

In embodiment, a new parameter-combination table of‘paraCombination-r18’ is designed, and the UE can be configured usingthe table for codebook parameters.

In one example, a new parameter-combination table of‘paraCombination-r18’ is codebook-common and the number of TRPs-common(i.e., N_(TRP)-common). Here the codebook-common means that a same tableis used for CB1 and CB2.

In one example, a new parameter-combination table of‘paraCombination-r18’ is codebook-specific and N_(TRP)-common. Forexample, as shown in FIG. 9 , a new parameter-combination table of‘paraCombination-r18’ is specifically designed for CB1 and CB2,respectively.

In one example, a new parameter-combination table of‘paraCombination-r18’ is codebook-common and N_(TRP)-specific. Forexample, as shown in FIG. 9 , a new parameter-combination table of‘paraCombination-r18’ is specifically designed for N_(TRP)=2,3,4.

In one example, a new parameter-combination table of‘paraCombination-r18’ is codebook-specific and N_(TRP)-specific. Forexample, as shown in FIG. 9 , for N_(TRP)=2,3,4, a newparameter-combination table of ‘paraCombination-r18’ is specificallydesigned for CB1 and CB2, respectively.

In one embodiment, a common table of ‘paraCombination-r18’ is designedfor both Rel-16 Type-II codebook-based mTRP CJT codebook and Type-IIport selection codebook-based mTRP CJT codebook. In other words, onecommon table is used for both the mTRP CJT codebooks design based onRel-16 Type-II (regular) codebook and Rel-17 Type-II port selectioncodebook. The UE can be configured using the table for codebookparameters for mTRP CJT codebooks.

In one example, the common table is designed using parameters (L, p, β)(similar to Rel-16 parameter combination). For example, any combinationof parameters for L, p, β described in certain embodiments herein can beincluded in the common table.

In one example, the common table is designed using parameters (M, α, β)(similar to Rel-17 parameter combination). For example, any combinationof parameters for M, α, β described in certain embodiments herein can beincluded in the common table.

In one example, the common table is designed using parameters (L, M, β).For example, any combination of parameters for L, M, β described incertain embodiments herein can be included in the common table.

In one example, the common table is designed using parameters (α, p, β).For example, any combination of parameters for a, p, β described incertain embodiments herein can be included in the common table.

In one example, the common table is designed using a combination oflegacy parameters (L, M, α, p, β). and new parameter value(s).

In one embodiment, a UE is configured with an mTRP (or D-MIMO or C-JT)codebook, via e.g., higher layer parameter codebookType set to‘typeII-r18-cjt’, which is designed based on Rel-16/17 Type-II codebook.For example, The mTRP codebook has a triple-stage structure which can berepresented as W=W₁W₂W_(f) ^(H), where the component W₁ is used toreport/indicate a spatial-domain (SD) basis matrix comprising SD basisvectors, the component W_(f) is used to report/indicate afrequency-domain (FD) basis matrix comprising FD basis vectors, and thecomponent W₂ is used to report/indicate coefficients corresponding to SDand FD basis vectors.

In one example, in Rel-16 Type-II codebook, L vectors, v_(m) ₁ _((i))_(,m) ₂ _((i)) , i=0, 1, . . . , L−1, are identified by the indicesq₁,q₂,n₁,n₂, indicated by i_(1,1), i_(1,2), obtained as in 5.2.2.2.3,where the values of C(x,y) are given in Table 5.2.2.2.5-4 of [9].

In Rel-18 Type-II codebook for multi-TRP, L_(n) SD basis vectors foreach TRP n can be selected/reported, where we denote that L_(n) is anumber of SD basis vectors for TRP n (CSI-RS resource n).

In one embodiment, on the SD basis selection for (Rel-18) Type-IIcodebook refinement for CJT mTRP, each of the {L_(n),n=1, . . . ,N_(TRP)} is configured by NW via higher-layer (RRC) signaling, whereN_(TRP) is a number of TRPs configured by the NW.

In one example, L_(n)∈{2,4,6}. In one example, L_(n)∈{1,2,4,6}. In oneexample, L_(n)∈{1,2,3,4,5,6}. In one example, In one example,L_(n)∈{1,2,3,4}. In one example, L_(n)∈{1,2,3}. In one example,L_(n)∈{1,2,4}. In one example, L_(n) can be selected from

n, where

_(n) is a subset of {1,2,3,4,5,6}.

In one embodiment, on the SD basis selection for (Rel-18) Type-IIcodebook refinement for CJT mTRP, L_(tot)=_(Σn=1) ^(N) ^(TRP) L_(n) isconfigured by NW via higher-layer (RRC) signaling and the relativevalue(s) of {L_(n),n=1, . . . , N_(TRP)} are reported by the UE, whereN_(TRP) is a number of TRPs configured by the NW. Although we denoteL_(tot) for Σ_(n=1) ^(N) ^(TRP) L_(n), another notation can be used forL_(tot), such as L_(sum), L′, L, etc. In one example, N_(TRP)∈{1,2,3,4}.

In one example, L_(tot) ∈{2N_(TRP), 4N_(TRP), 6N_(TRP)}. In one example,L_(tot) ∈{1N_(TRP), 2N_(TRP), 4N_(TRP), 6N_(TRP)}. In one example,L_(tot) ∈{1N_(TRP), 2N_(TRP), 3N_(TRP), 4N_(TRP), 5N_(TRP), 6N_(TRP)}.In one example, In one example, L_(tot) ∈{1N_(TRP), 2N_(TRP), 3N_(TRP),4N_(TRP)}. In one example, L_(tot)∈{1N_(TRP), 2N_(TRP), 3N_(TRP)}.

In one example, L_(tot)∈{1N_(TRP), 2N_(TRP), 4N_(TRP)}. In one example,L_(tot) can be selected from

_(tot), where

_(tot) is a subset of {1, . . . ,24}.

In one example, L_(tot) ∈

_(tot,1) for N_(TRP)≥x and L_(tot) ∈

_(tot,2) for N_(TRP)<X, where

_(tot,1) and

_(tot,2) is a subset of {1, . . . ,24} and x=1, 2, 3, or 4.

In one example, L_(tot) ∈

_(tot,1) for N_(TRP)>x and L_(tot) ∈

_(tot,2) for N_(TRP)≤x, where

_(tot,1) and

_(tot,2) is a subset of {1, . . . ,24} and x=1, 2, 3, or 4.

In one example, {L_(n), n=1, . . . , N_(TRP)} are explicitly reportedvia a joint indicator or separate multiple indicators in CSI part 1. Forexample, a joint indicator can be used to indicate (L₁, . . . , L_(N)_(TRP) ) under the constraint of L_(tot)=_(n=1) ^(N) ^(TRP) L_(n) andL_(n)≥0, for n=1, . . . , N_(TRP) where L_(n) is a non-negative integer.In another example, an indicator can be used to indicate each L_(n) forn=1, . . . , N_(TRP) under the constraint of L_(tot)=Σ_(n=1) ^(N) ^(TRP)and L_(n)≥0.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW. For any TRP n where L_(n)=0(i.e., no SD beam selection case) and/or where TRP n is not selectedwhich can be indicated via N_(TRP)-bit bitmap in CSI part 1, no SD basisvector for TRP n is reported, hence no payload is induced.

-   -   In one example, a joint indicator to indicate {Ln} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\Sigma}_{n = 1}^{N_{TRP}}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width). For any TRP n where L_(n)=0 (i.e., no SD beamselection case) and/or where TRP n is not selected which can beindicated via N_(TRP)-bit bitmap in CSI part 1, no SD basis vector forTRP n is reported, hence no additional payload is induced in the sum.

In one example, L_(n)s associated with TRPs that are selected areexplicitly reported via a joint indicator or separate multipleindicators in CSI part 1. In CSI part 1, N_(TRP)-bit bitmap is used toindicate selected N TRPs out of N_(TRP) TRPs. For example, whenN_(TRP)=4 and N_(TRP)-bit bitmap is ‘1001’ in CSI part 1, the first TRPand the fourth TRP are selected. In this example, L_(n) associated withthe selected TRPs are explicitly reported.

-   -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n∈s) under the constraint of L_(tot)=Σ_(n∈S)L_(n) and        L_(n)≥1, for n∈S where L_(n) is a positive integer and S is a        set of selected TRP indexes (i.e., a subset of {1, 2, . . . ,        N_(TRP)}.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n=1) ^(N) under the constraint of L_(tot)=Σ_(n=1)        ^(N)L_(n) and L_(n)≥1, for n=1, . . . , N where L_(n) is a        positive integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈S under the constraint of L_(tot)=Σ_(n∈S)L_(n) and L_(n)≥1        where L_(n) is a positive integer and S is a set of selected TRP        indexes (i.e., a subset of {1,2, . . . , N_(TRP)}.    -   In one example, an indicator can be used to indicate each L_(n)        for n=1, . . . , N under the constraint of L_(tot)=Σ_(n=1)        ^(N)L_(n) and L_(n)≥1, for n=1, . . . , N where L_(n) is a        positive integer.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW, where n∈S or n=1, . . . , N.

-   -   In one example, a joint indicator to indicate {L_(n)} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\Sigma}_{n = 1}^{N}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits or

$\left\lceil {\log_{2}{\Sigma}_{n \in S}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits.

In one example, L_(n)s associated with TRPs that are selected areexplicitly reported via a joint indicator or separate multipleindicators in CSI part 2. The remaining part is similar to otherexamples described herein.

In one example, some of {L_(n), n=1, . . . , N_(TRP)} are explicitlyreported via a joint indicator or separate multiple indicators in CSIpart 1 and the others of {L_(n), n=1, . . . , N_(TRP)} are reportedimplicitly (or determined implicitly hence not explicitly reported).

-   -   In one example, a joint indicator can be used to indicate (L₁, .        . . , L_(N) _(TRP) ⁻¹), (i.e., excluding L with the highest        index), and L_(N) _(TRP) is implicitly determined by (L₁, . . .        , L_(N) _(TRP) ⁻¹) and L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence        L_(N) _(TRP) is not reported. Here, L_(n)≥0,for n=1, . . . ,        N_(TRP)−1 where L_(n) is a non-negative integer.    -   In one example, a joint indicator can be used to indicate (L₂, .        . . , L_(N) _(TRP) ), (i.e., excluding L with the lowest index),        and L₁ is implicitly determined by (L₂, . . . , L_(N) _(TRP) )        and L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence L₁ is not reported.        Here, L≥0,for n=2, . . . , N_(TRP) where L_(n) is a non-negative        integer.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n∈{1, . . . , N) _(TRP) _(} \{n*}) (i.e., excluding L        with a reference TRP index n*, which can be determined by UE or        configured by NW or determined by a pre-defined rule), and        L_(n)* is implicitly determined by {L_(n)}_(n∈{1, . . . , N)        _(TRP) _(} \{n*}) and L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence        L_(n*) is not reported. Here, L_(n)≥0, for n∈{1, . . . ,        N_(TRP)}\{n*} where L_(n) is a non-negative integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n=1, . . . , N_(TRP)−1 (i.e., excluding L with the highest        index), and L_(N) _(TRP) is implicitly determined by L₁, . . . ,        L_(N) _(TRP) ⁻¹ and L_(tot)=Σ_(n=1) ^(N) ^(TRP) hence L_(N)        _(TRP) is not reported. Here, L_(n)≥0, for n=1, . . . ,        N_(TRP)−1 where L_(n) is a non-negative integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n=2, . . . , N_(TRP) (i.e., excluding L with the lowest        index), and L₁ is implicitly determined by L₂, . . . , L_(N)        _(TRP) and L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence L₁ is not        reported. Here, L_(n)≥0, for n=2, . . . , N_(TRP) where L_(n) is        a non-negative integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈{1, . . . , N_(TRP)}\{n*} (i.e., excluding L with a        reference TRP index n*, which can be determined by UE or        configured by NW or determined by a pre-defined rule), and        L_(n*) is implicitly determined by {Ln}_(n∈{1, . . . , N) _(TRP)        _(} \{n*}) and L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence L_(n*) is        not reported. Here, L_(n)≥0, for n∈{1, . . . , N_(TRP)} \{n*}        where L_(n) is a non-negative integer.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW. For any TRP n where L_(n)=0(i.e., no SD beam selection case) and/or where TRP n is not selectedwhich can be indicated via N_(TRP)-bit bitmap in CSI part 1, no SD basisvector for TRP n is reported, hence no payload is induced.

-   -   In one example, a joint indicator to indicate {Ln} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\Sigma}_{n = 1}^{N_{TRP}}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width). For any TRP n where L_(n)=0 (i.e., no SD beamselection case) and/or where TRP n is not selected which can beindicated via N_(TRP)-bit bitmap in CSI part 1, no SD basis vector forTRP n is reported, hence no additional payload is induced in the sum.

In one example, some of L_(n)s associated with TRPs that are selectedare explicitly reported via a joint indicator or separate multipleindicators in CSI part 1 and the others of L_(n)s associated with TRPsthat are selected are reported implicitly (or determined implicitlyhence not explicitly reported). In CSI part 1, N_(TRP)-bit bitmap isused to indicate selected N TRPs out of N_(TRP) TRPs. For example, whenN_(TRP)=4 and N_(TRP)-bit bitmap is ‘1001’ in CSI part 1, the first TRPand the fourth TRP are selected. In this example, some of L_(n)associated with the selected TRPs are explicitly reported and the othersare implicitly determined.

In one example, a joint indicator can be used to indicate{L_(n)}_(n∈s\{n) _(Low) _(}) and L_(n) _(Low) is implicitly determinedby {L_(n)}_(n∈s\{n) _(Low) _(}) and L_(tot)=Σ_(n∈S)L_(n) and L_(n)≥1 forn∈S \ {n_(Low)} where L_(n) is a positive integer and S is a set ofselected TRP indexes (i.e., a subset of {1,2, . . . , N_(TRP)}) andn_(Low) is the lowest index in S.

In one example, a joint indicator can be used to indicate{L_(n)}_(n∈s\{n) _(High) _(}) and L_(n) _(High) is implicitly determinedby {L_(n)}_(n∈s\{n) _(High) _(}) and L_(tot)=Σ_(n∈S)L_(n) and L_(n)≥1for n∈S\ {n_(High)} where L_(n) is a positive integer and S is a set ofselected TRP indexes (i.e., a subset of {1,2, . . . , N_(TRP)}) andn_(High) is the highest index in S.

-   -   In one example, a joint indicator can be used to indicate        {Ln}n∈_(s\{n*}) and L_(n*) is implicitly determined by        {L_(n)}_(n∈S\{n*}) and L_(tot)=Σ_(n∈S)L_(n) and L_(n)≥1 for n∈S        544 {n*} where L_(n) is a positive integer and S is a set of        selected TRP indexes (i.e., a subset of {1,2, . . . , N_(TRP)})        and n* is a reference TRP index in S, which can be determined by        UE or configured by NW or determined by a pre-defined rule.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n=1) ^(N=1) and L_(N) is implicitly determined by        {L_(n)}_(n=1) ^(N=1) and L_(tot)=Σ_(n=1) ^(N) L_(n) and L_(n)≥1,        for n=1, . . . , N−1 where L_(n) is a positive integer.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n=2) ^(N) and L₁ is implicitly determined by        {L_(n)}_(n=2) ^(N) and L_(tot)=Σ_(n=1) ^(N) L_(n) and L_(n)≥1,        for n=2, . . . , N where L_(n) is a positive integer.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n∈{1, . . . , N}\{n*}) and L_(n*) is implicitly        determined by {L_(n)}_(n∈{1, . . . , N}\{n*}) and        L_(tot)=Σ_(n=1) ^(N)L_(n) and L_(n)≥1, for n∈{1, . . . , N}        \{n*} where L_(n) is a positive integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈S\{n_(Low)} and L_(n) _(Low) is implicitly determined by        {L_(n)}_(n∈S\{n) _(Low) _(}) and L_(tot)=Σ_(n∈S)L_(n) and        L_(n)≥1 for n∈S\ {n_(Low)} where L_(n) is a positive integer and        S is a set of selected TRP indexes (i.e., a subset of {1,2, . .        . , N_(TRP)}) and n_(Low) is the lowest index in S.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈S\{n_(High)} and L_(n) _(High) is implicitly determined by        {L_(n)}_(n∈s\{n) _(High) _(}) and L_(tot)=Σ_(n∈S)L_(n) and        L_(n)≥1 for n∈S\{n_(High)} where L_(n) is a positive integer and        S is a set of selected TRP indexes (i.e., a subset of {1,2, . .        . , N_(TRP)}) and n_(High) is the highest index in S.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈S\{n*} and L_(n{) _(n*) _(}) is implicitly determined by        {L_(n)}_(n∈S\{n*}) and L_(tot)=Σ_(n∈S)L_(n) and L_(n)≥1 for        n∈S\{n*} where L_(n) is a positive integer and S is a set of        selected TRP indexes (i.e., a subset of {1,2, . . . , N_(TRP)})        and n* is a reference TRP index in S, which can be determined by        UE or configured by NW or determined by a pre-defined rule.    -   In one example, an indicator can be used to indicate each L_(n)        for n=1, . . . , N−1 and L_(N) is implicitly determined by        {L_(n)}_(n=1) ^(N-1) and L_(tot)=Σ_(n=1) ^(N)L_(n) and L_(n)≥1,        for n=1, . . . , N−1 where L_(n) is a positive integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n=2, . . . , N and L₁ is implicitly determined by        {L_(n)}_(n∈{1, . . . , N}\{n*}) and L_(tot)=Σ_(n=1) ^(N)L_(n)        and L_(n)≥1, for n∈{1, . . . , N}\{n*} where L_(n) is a positive        integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈{1, . . . , N} \{n*} and L_(n*) is implicitly determined        by {L_(n)}_(n∈{1, . . . , N}\{n*}) and L_(tot)=Σ_(n=1) ^(N)L_(n)        and L_(n)≥1, for n∈{1, . . . , N}\{n*} where L_(n) is a positive        integer.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW, where n∈S or n=1, . . . , N.

-   -   In one example, a joint indicator to indicate {L_(n)} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\sum}_{n = 1}^{N}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits or

$\left\lceil {\log_{2}{\sum}_{n \in S}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits.

In one example, some of L_(n)s associated with TRPs that are selectedare explicitly reported via a joint indicator or separate multipleindicators in CSI part 2 and the others of L_(n)s associated with TRPsthat are selected are reported implicitly (or determined implicitlyhence not explicitly reported). The remaining part is similar to otherexamples described herein.

In one example, {L_(n), n=1, . . . , N_(TRP)} are reported implicitly,according to at least one of the following examples.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N_(TRP) TRPs and the selection ofL_(tot) SD basis vectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{TRP}N_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 1. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each TRP.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N_(TRP) TRPs and the selection ofL_(tot) SD basis vectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{TRP}N_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 2. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each TRP.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N TRPs, where N is a number ofselected TRPs. For example, in CSI part 1, N_(TRP)-bit bitmap is used toindicate selected N TRPs out of N_(TRP) TRPs. For example, whenN_(TRP)=4 and N_(TRP)-bit bitmap is ‘1001’ in CSI part 1, the first TRPand the fourth TRP are selected. The selection of L_(tot) SD basisvectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{{NN}_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 1. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each of the selected TRPs.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N TRPs, where N is a number ofselected TRPs. For example, in CSI part 1, N_(TRP)-bit bitmap is used toindicate selected N TRPs out of N_(TRP) TRPs. For example, whenN_(TRP)=4 and N_(TRP)-bit bitmap is ‘1001’ in CSI part 1, the first TRPand the fourth TRP are selected. The selection of L_(tot) SD basisvectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{{NN}_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 2. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each of the selected TRPs.

In one example, for a given L_(tot), a set

for the value of L_(n) for n=1, . . . , N_(TRP) is predetermined and anelement of the set is selected and reported. For example, a combinationof the elements each of which corresponds to L_(n) is reported via ajoint indicator or separate multiple indicators (that indicate(s) theindex of the selected element in the set) in CSI part 1.

In one example,

is a subset of {1,2, . . . , L_(tot)}. In one example,

is a subset of {1, 2, . . . , 6}. For example,

={1,2,4,6}. For example,

={1,2,3,4}. For example,

={2,4,6}. For example,

={2,3,4}.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW. For any TRP n where L_(n)=0(i.e., no SD beam selection case) and/or where TRP n is not selectedwhich can be indicated via N_(TRP)-bit bitmap in CSI part 1, no SD basisvector for TRP n is reported, hence no payload is induced.

-   -   In one example, a joint indicator to indicate {Ln} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\sum}_{n = 1}^{N_{TRP}}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width). For any TRP n where L_(n)=0 (i.e., no SD beamselection case) and/or where TRP n is not selected which can beindicated via N_(TRP)-bit bitmap in CSI part 1, no SD basis vector forTRP n is reported, hence no additional payload is induced in the sum.

In one example, for a given L_(tot), a set

for the value of L_(n) for n∈S or n=1, . . . , N is predetermined and anindex of the set is selected and reported, where S is a set of selectedTRPs. (For example, in CSI part 1, N_(TRP)-bit bitmap is used toindicate selected N TRPs out of N_(TRP) TRPs. For example, whenN_(TRP)=4 and N_(TRP)-bit bitmap is ‘1001’ in CSI part 1, the first TRPand the fourth TRP are selected.) In one example, a combination ofindexes each of which corresponds to L_(n) is reported via a jointindicator or separate multiple indicators in CSI part 1.

In one example,

is a subset of {1,2, . . . , L_(tot)}. In one example,

is a subset of {1, 2, . . . , 6}. For example,

={1,2,4,6}. For example,

={1,2,3,4}. For example, £={2,4,6}. For example, £={2,3,4}.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW, where n∈S or n=1, . . . , N.

-   -   In one example, a joint indicator to indicate {Ln} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\sum}_{n = 1}^{N}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits or

$\left\lceil {\log_{2}{\sum}_{n \in S}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits.

In one example, for a given L_(tot), a set for the value of L_(n) forn∈S or n=1, . . . , N is predetermined and an index of the set isselected and reported, where S is a set of selected TRPs. (For example,in CSI part 1, N_(TRP)-bit bitmap is used to indicate selected N TRPsout of N_(TRP) TRPs. For example, when N_(TRP)=4 and N_(TRP)-bit bitmapis ‘1001’ in CSI part 1, the first TRP and the fourth TRP are selected.)In one example, a combination of indexes each of which corresponds toL_(n) is reported via a joint indicator or separate multiple indicatorsin CSI part 2. The remaining part is similar to or same as otherexamples described herein.

In one embodiment, on the SD basis selection for (Rel-18) Type-IIcodebook refinement for CJT mTRP, an L parameter is configured by NW viahigher-layer (RRC) signaling and {Ln, n=1, . . . , N_(TRP)} aredetermined from the value of L, where N_(TRP) is a number of TRPsconfigured by the NW. In one example, N_(TRP) ∈{1,2,3,4}.

In one example, one L value is associated with a reference TRP n* andanother value determined from L is associated with the remainingN_(TRP)−1 (or N−1) TRPs. In one example,

$L_{n^{*}} = {{L{and}L_{n}} = {{\left\lceil \frac{L}{2} \right\rceil{for}n} \neq {n^{*}.}}}$

In one example,

${L_{n^{*}} = {{L{and}L_{n}} = {{\left\lceil \frac{L}{x} \right\rceil{for}n} \neq n^{*}}}},$wherex = 2, 3, or4,

. . . and so on.

-   -   In one example, a reference TRP n* is configured by NW.    -   In one example, a reference TRP n* is determined by UE and        reported in CSI part 1 or CSI part 2.    -   In one example, a reference TRP n* is fixed to 1 or the last        index, e.g., N_(TRP) or N, or another value n* ∈{1, . . . ,        N_(TRP)}

In one embodiment, on the SD basis selection for (Rel-18) Type-IIcodebook refinement for CJT mTRP, L_(max)≥Σ_(n=1) ^(N) ^(TRP) L_(n) isconfigured by NW via higher-layer (RRC) signaling and the relativevalue(s) of {L_(n), n=1, . . . , N_(TRP)} are reported by the UE, whereN_(TRP) is a number of TRPs configured by the NW. Although we denoteL_(max) for an upper bound of Σ_(n=1) ^(N) ^(TRP) L_(n), anothernotation can be used for L_(max), such as L_(sum), L′, L, etc. In oneexample, N_(TRP) ∈{1,2,3,4}.

In one example, L_(max) ∈{2N_(TRP), 4N_(TRP), 6N_(TRP)}. In one example,L_(max)∈{1N_(TRP), 2N_(TRP), 4N_(TRP), 6N_(TRP)}.

In one example, L_(max)∈{1N_(TRP), 2N_(TRP), 3N_(TRP), 4N_(TRP),5N_(TRP), 6N_(TRP)}. In one example, In one example, L_(max)∈{1N_(TRP),2N_(TRP), 3N_(TRP), 4N_(TRP)}. In one example, L_(max)∈{1N_(TRP),2N_(TRP), 3N_(TRP)}.

In one example, L_(max)∈{1N_(TRP), 2N_(TRP), 4N_(TRP)}. In one example,L_(max) can be selected from

_(max), where

_(max) is a subset of {1, . . . , 24}.

In one example, L_(max)∈

_(max,1) for N_(TRP)>x and L_(max)∈

_(max,2) for N_(TRP)≤x, where

_(max,1) and

_(max,2) is a subset of {1, . . . , 24} and x=1, 2, 3, or 4.

In one example, L_(max)∈

_(max,1) for N_(TRP)>x and L_(max)∈

_(max,2) for N_(TRP)≤x, where

_(max,1) and

_(max,2) is a subset of {1, . . . , 24} and x=1, 2, 3, or 4.

In one example, {L_(n), n=1, . . . , N_(TRP)} are explicitly reportedvia a joint indicator or separate multiple indicators in CSI part 1. Forexample, a joint indicator can be used to indicate (L₁, . . . , L_(N)_(TRP) ) under the constraint of L_(max) Σ_(n=1) ^(N) ^(TRP) L_(n) andL_(n)≥0, for n=1, . . . , N_(TRP) where L_(n) is a non-negative integer.In another example, an indicator can be used to indicate each L_(n) forn=1, . . . , N_(TRP) under the constraint of L_(max)≥Σ_(n=1) ^(N) ^(TRP)L_(n) and L_(n)≥0. In one example, each L_(n) is selected from a set

and indicated via ┌log₂|

|┐-bit indicator. So, in this case, N_(TRP) ┌log₂|

|┐-bit indicators can be used. In one example,

∈{2,4}. In one example,

∈{2,4,6}. In one example,

∈{1,2,3,4}. In one example,

∈{1,2,3,4,5,6}. In one example,

∈{1,2,4}. In one example,

∈{1,2,3}. In one example,

is a subset of {1,2,3,4,5,6}.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW. For any TRP n where L_(n)=0(i.e., no SD beam selection case) and/or where TRP n is not selectedwhich can be indicated via N_(TRP)-bit bitmap in CSI part 1, no SD basisvector for TRP n is reported, hence no payload is induced.

-   -   In one example, a joint indicator to indicate {Ln} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\sum}_{n = 1}^{N_{TRP}}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width). For any TRP n where L_(n)=0 (i.e., no SD beamselection case) and/or where TRP n is not selected which can beindicated via N_(TRP)-bit bitmap in CSI part 1, no SD basis vector forTRP n is reported, hence no additional payload is induced in the sum.

In one example, L_(n)s associated with TRPs that are selected areexplicitly reported via a joint indicator or separate multipleindicators in CSI part 1. In CSI part 1, N_(TRP)-bit bitmap is used toindicate selected N TRPs out of N_(TRP) TRPs. For example, whenN_(TRP)=4 and N_(TRP)-bit bitmap is ‘1001’ in CSI part 1, the first TRPand the fourth TRP are selected. In this example, L_(n) associated withthe selected TRPs are explicitly reported.

-   -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n∈s) under the constraint of L_(max)≥Σ_(n∈S) L_(n) and        L_(n)≥1, for n∈S where L_(n) is a positive integer and S is a        set of selected TRP indexes (i.e., a subset of {1,2, . . . ,        N_(TRP)}.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n=1) ^(N) under the constraint of L_(max)≥Σ_(n=1)        ^(N)L_(n) and L_(n)≥1, for n=1, . . . , N where L_(n) is a        positive integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈S under the constraint of L_(max)≥Σ_(n∈S)L_(n) and L_(n)≥1        where L_(n) is a positive integer and S is a set of selected TRP        indexes (i.e., a subset of {1,2, . . . , N_(TRP)}. In one        example, each L_(n) is selected from a set        and indicated via ┌log₂|        |┐-bit indicator. So, in this case, N ┌log₂|        |┐-bit indicators can be used. In one example,        ∈{2,4}. In one example,        ∈{2,4,6}. In one example,        ∈{1,2,3,4}. In one example,        ∈{1,2,3,4,5,6}. In one example,        ∈{1,2,4}. In one example,        ∈{1,2,3}. In one example,        is a subset of {1,2,3,4,5,6}.    -   In one example, an indicator can be used to indicate each L_(n)        for n=1, . . . , N under the constraint of L_(max)≥Σ_(n=1)        ^(N)L_(n) and L_(n)≥1, for n=1, . . . , N where L_(n) is a        positive integer. In one example, each L_(n) is selected from a        set L and indicated via ┌log₂|        |┐-bit indicator. So, in this case, N ┌log₂|        |┐-bit indicators can be used. In one example,        ∈{2,4}. In one example,        ∈{2,4,6}. In one example,        ∈{1,2,3,4}. In one example,        ∈{1,2,3,4,5,6}. In one example,        ∈{1,2,4}. In one example,        ∈{1,2,3}. In one example, £ is a subset of 11,2,3,4,5,61.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW, where n∈S or n=1, . . . , N.

-   -   In one example, a joint indicator to indicate {L_(n)} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\sum}_{n = 1}^{N}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits or

$\left\lceil {\log_{2}{\sum}_{n \in S}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits.

In one example, L_(n)s associated with TRPs that are selected areexplicitly reported via a joint indicator or separate multipleindicators in CSI part 2. The remaining part is similar to otherexamples described herein. For example, when N_(TRP)=4 and N_(TRP)-bitbitmap is ‘1001’ in CSI part 1, the first TRP and the fourth TRP areselected. In this example, L_(n) associated with the selected TRPs areexplicitly reported.

-   -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n∈S) under the constraint of L_(max)≥Σ_(n∈S) L_(n) and        L_(n)≥1, for n∈S where L_(n) is a positive integer and S is a        set of selected TRP indexes (i.e., a subset of {1,2, . . . ,        N_(TRP)}.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n=1) ^(N) under the constraint of L_(max)≥Σ_(n=1)        ^(N)L_(n) and L_(n)≥1, for n=1, . . . , N where L_(n) is a        positive integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈S under the constraint of L_(max)≥Σ_(n∈S)L_(n) and L_(n)≥1        where L_(n) is a positive integer and S is a set of selected TRP        indexes (i.e., a subset of {1,2, . . . , N_(TRP)}. In one        example, each L_(n) is selected from a set        and indicated via ┌log₂|        |┐-bit indicator. So, in this case, N ┌log₂|        |┐-bit indicators can be used. In one example,        ∈{2,4}. In one example,        ∈{2,4,6}. In one example,        ∈{1,2,3,4}. In one example,        ∈{1,2,3,4,5,6}. In one example,        ∈{1,2,4}. In one example,        ∈{1,2,3}. In one example,        is a subset of {1,2,3,4,5,6}.    -   In one example, an indicator can be used to indicate each L_(n)        for n=1, . . . , N under the constraint of L_(max)≥_(Σn=1) ^(N)        L_(n) and L_(n)≥1, for n=1, . . . , N where L_(n) is a positive        integer. In one example, each L_(n) is selected from a set        and indicated via ┌log₂|        |┐-bit indicator. So, in this case, N ┌log₂|        |┐-bit indicators can be used. In one example,        ∈{2,4}. In one example,        ∈{2,4,6}. In one example,        ∈{1,2,3,4}. In one example,        ∈{1,2,3,4,5,6}. In one example,        ∈{1,2,4}. In one example,        ∈{1,2,3}. In one example,        is a subset of {1,2,3,4,5,6}.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW, where n∈S or n=1, . . . , N.

-   -   In one example, a joint indicator to indicate {L_(n)} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\sum}_{n = 1}^{N}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits or

$\left\lceil {\log_{2}{\sum}_{n \in S}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits.

In one embodiment, L_(tot) is determined by UE whereL_(max)≥L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) and the determined L_(tot) isreported in CSI part 1. In one example, an indicator to indicate L_(tot)has the size of payload ┌log₂ L_(max)┐ bits, i.e., L_(tot) is selectedfrom {1,2, . . . , L_(max)}. In another example, an indicator toindicate L_(tot) has the size of payload ┌log₂|

_(tot)|┐ bits, where

_(tot) is a set including L_(max) and positive integers less than orequal to L_(max), and |

_(tot)| is a number of the elements in

_(tot). In one example,

_(tot) can be any subset of {1,2, . . . , L_(max)}. In one example,

_(tot) can be any subset of

$\left\{ {\left\lceil \frac{L_{\max}}{4} \right\rceil,\left\lceil \frac{L_{\max}}{3} \right\rceil,\left\lceil \frac{L_{\max}}{2} \right\rceil,L_{\max}} \right\}.$

In one example, L_(tot)∈{2N_(TRP), 4N_(TRP), 6N_(TRP)}. In one example,L_(tot) ∈{1N_(TRP), 2N_(TRP), 4N_(TRP), 6N_(TRP)}. In one example,L_(tot) ∈{1N_(TRP), 2N_(TRP), 3N_(TRP), 4N_(TRP), 5N_(TRP), 6N_(TRP)}.In one example, In one example, L_(tot) ∈{1N_(TRP), 2N_(TRP), 3N_(TRP),4N_(TRP)}. In one example, L_(tot)∈{1N_(TRP), 2N_(TRP), 3N_(TRP)}.

In one example, L_(tot)∈{1N_(TRP), 2N_(TRP), 4N_(TRP)}. In one example,L_(tot) can be selected from a subset of {1, . . . , 24}.

In one example, L_(tot)∈{2N_(TRP), 4N_(TRP), 6N_(TRP)}∩{1,2, . . . ,L_(max)}. In one example, L_(tot) ∈{1N_(TRP), 2N_(TRP), 4N_(TRP),6N_(TRP)}∩{1,2, . . . , L_(max)}. In one example, L_(tot) ∈{1N_(TRP),2N_(TRP), 3N_(TRP), 4N_(TRP), 5N_(TRP), 6N_(TRP)}∩{1,2, . . . ,L_(max)}. In one example, In one example, L_(tot)∈{1N_(TRP), 2N_(TRP),3N_(TRP), 4N_(TRP)}∩{1,2, . . . , L_(max)}. In one example, L_(tot)∈{1N_(TRP), 2N_(TRP), 3N_(TRP)}∩{1,2, . . . , L_(max)}.

In one example, L_(tot)∈{1N_(TRP), 2N_(TRP), 4N_(TRP)}∩{1,2, . . . ,L_(max)}. In one example, L_(tot) can be selected from a subset of {1, .. . , 24}∩{1, 2, . . . , L_(max)}.

In one example, some of {Ln, n=1, . . . , N_(TRP)} are explicitlyreported via a joint indicator or separate multiple indicators in CSIpart 1 and the others of {L_(n), n=1, . . . , L_(N) _(TRP) ⁻¹} arereported implicitly (or determined implicitly hence not explicitlyreported).

-   -   In one example, a joint indicator can be used to indicate (L₁, .        . . , L_(N) _(TRP) ⁻¹), (i.e., excluding L with the highest        index), and L_(N) _(TRP) is implicitly determined by (L₁, . . .        , L_(N) _(TRP) ⁻¹) and L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence        L_(N) _(TRP) is not reported. Here, L_(n)≥0, for n=1, . . . ,        N_(TRP)−1 where L_(n) is a non-negative integer.    -   In one example, a joint indicator can be used to indicate (L₂, .        . . , L_(N) _(TRP) ), (i.e., excluding L with the lowest index),        and L₁ is implicitly determined by (L₂, . . . , L_(N) _(TRP) )        and L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence L₁ is not reported.        Here, L_(n)≥0,for n=2, . . . , N_(TRP) where L_(n) is a        non-negative integer.

In one example, a joint indicator can be used to indicate{L_(n)}_(n∈{1, . . . , N) _(TRP) _(}\{n*}) (i.e., excluding L with areference TRP index n*, which can be determined by UE or configured byNW or determined by a pre-defined rule), and Ln* is implicitlydetermined by {L_(n)}_(n∈{1, . . . , N) _(TRP) _(}\{n*}) andL_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence L_(n*) is not reported. Here,L_(n)≥0, for n∈{1, . . . , N_(TRP)}\{n*} where L_(n) is a non-negativeinteger.

-   -   In one example, an indicator can be used to indicate each L_(n)        for n=1, . . . , N_(TRP)−1 (i.e., excluding L with the highest        index), and L_(N) _(TRP) is implicitly determined by L₁, . . . ,        L_(N) _(TRP) ⁻¹ and L_(tot)=Σ_(n=1) ^(N) ^(TRP) hence L_(N)        _(TRP) is not reported. Here, L_(n)≥0, for n=1, . . . ,        N_(TRP)−1 where L_(n) is a non-negative integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n=2, . . . , N_(TRP) (i.e., excluding L with the lowest        index), and L₁ is implicitly determined by L₂, . . . , L_(N)        _(TRP) and L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence L₁ is not        reported. Here, L_(n)≥0, for n=2, . . . , N_(TRP) where L_(n) is        a non-negative integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈{1, . . . , N_(TRP)} \{n*} (i.e., excluding L with a        reference TRP index n*, which can be determined by UE or        configured by NW or determined by a pre-defined rule), and Ln.        is implicitly determined by {L_(n)}_(n∈{1, . . . , N) _(TRP)        _(}\{n*}) and L_(tot)=Σ_(n=1) ^(N) ^(TRP) L_(n) hence L_(n*) is        not reported. Here, L_(n)≥0, for n∈{1, . . . , N_(TRP)} \{n*}        where L_(n) is a non-negative integer.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

-   -   In one example, an indicator to indicate (each) L_(n) SD basis        vectors has the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW. For any TRP n where L_(n)=0(i.e., no SD beam selection case) and/or where TRP n is not selectedwhich can be indicated via N_(TRP)-bit bitmap in CSI part 1, no SD basisvector for TRP n is reported, hence no payload is induced.

-   -   In one example, a joint indicator to indicate {L_(n)} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\sum}_{n = 1}^{N_{TRP}}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width). For any TRP n where L_(n)=0 (i.e., no SD beamselection case) and/or where TRP n is not selected which can beindicated via N_(TRP)-bit bitmap in CSI part 1, no SD basis vector forTRP n is reported, hence no additional payload is induced in the sum.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N_(TRP) TRPs and the selection ofL_(tot) SD basis vectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{TRP}N_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 1. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each TRP.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N_(TRP) TRPs and the selection ofL_(tot) SD basis vectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{TRP}N_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 2. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each TRP.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N TRPs, where N is a number ofselected TRPs. For example, in CSI part 1, N_(TRP)-bit bitmap is used toindicate selected N TRPs out of N_(TRP) TRPs. For example, whenN_(TRP)=4 and N_(TRP)-bit bitmap is ‘1001’ in CSI part 1, the first TRPand the fourth TRP are selected. The selection of L_(tot) SD basisvectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{NN_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 1. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each of the selected TRPs.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N TRPs, where N is a number ofselected TRPs. For example, in CSI part 1, N_(TRP)-bit bitmap is used toindicate selected N TRPs out of N_(TRP) TRPs. For example, whenN_(TRP)=4 and N_(TRP)-bit bitmap is ‘1001’ in CSI part 1, the first TRPand the fourth TRP are selected. The selection of L_(tot) SD basisvectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{NN_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 2. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each of the selected TRPs.

In one embodiment, L_(tot) is determined by UE whereL_(max)≥L_(tot)=Σ_(n=1) ^(N)L_(n) (or L_(max)≥L_(tot)=Σ_(n∈s)L_(n)), andthe determined L_(tot) is reported in CSI part 1. Here, N is a number ofselected TRPs out of N_(TRP) TRPs and S is a set of selected TRP indexes(i.e., a subset of {1,2, . . . , N_(TRP)}). Note that in CSI part 1,N_(TRP)-bit bitmap can be used to indicate selected N TRPs out ofN_(TRP) TRPs. In one example, an indicator to indicate L_(tot) has thesize of payload ┌log₂ L_(max)┐ bits, i.e., L_(tot) is selected from{1,2, . . . , L_(max)}. In another example, an indicator to indicateL_(tot) has the size of payload ┌log₂|

_(tot)|┐ bits, where

_(tot) is a set including L_(max) and positive integers less than orequal to L_(max), and |

_(tot)| is a number of the elements in

_(tot). In one example,

_(tot) can be any subset of {1,2, . . . , L_(max)}. In one example,L_(tot) can be any subset of

$\left\{ {\left\lceil \frac{L_{\max}}{4} \right\rceil,\left\lceil \frac{L_{\max}}{3} \right\rceil,\left\lceil \frac{L_{\max}}{2} \right\rceil,L_{\max}} \right\}.$

In one example, an indicator to indicate L_(tot) has the size of payload

${\left\lceil {\log_{2}\left( {L_{\max} \cdot \frac{N}{N_{TRP}}} \right)} \right\rceil{bits}},$

i.e., L_(tot) is selected from

$\left\{ {{1,2},\ldots,\left\lceil {L_{\max} \cdot \frac{N}{N_{TRP}}} \right\rceil} \right\}.$

In one example, L_(tot)∈{2N, 4N, 6N}. In one example, L_(tot)∈{1N, 2N,4N, 6N}. In one example, L_(tot)∈{1N, 2N, 3N, 4N, 5N, 6N}. In oneexample, In one example, L_(tot) ∈{1N, 2N, 3N, 4N}. In one example,L_(tot)∈{1N, 2N, 3N}.

In one example, L_(tot)∈{1N, 2N, 4N}. In one example, L_(tot) can beselected from a subset of {1, . . . , 24}.

In one example, L_(tot)∈{2N, 4N, 6N}∩{1,2, . . . , L_(max)}. In oneexample, L_(tot) ∈{1N, 2N, 4N, 6N}∩{1,2, . . . , L_(max)}. In oneexample, L_(tot)∈{1N, 2N, 3N, 4N, 5N, 6N}∩{1,2, . . . , L_(max)}. In oneexample, In one example, L_(tot)∈{1N,2N,3N,4N}∩{1,2, . . . , L_(max)}.In one example, L_(tot)∈{1N, 2N, 3N}∩{1,2, . . . , L_(max)}.

In one example, L_(tot)∈{1N, 2N, 4N}∩{1,2, . . . , L_(max)}. In oneexample, L_(tot) can be selected from a subset of {1, . . . , 24}∩{1, 2,. . . , L_(max)}.

In one example, some of L_(n)s associated with TRPs that are selectedare explicitly reported via a joint indicator or separate multipleindicators in CSI part 1 and the others of L_(n)s associated with TRPsthat are selected are reported implicitly (or determined implicitlyhence not explicitly reported). In CSI part 1, N_(TRP)-bit bitmap isused to indicate selected N TRPs out of N_(TRP) TRPs. For example, whenN_(TRP)=4 and N_(TRP)-bit bitmap is ‘1001’ in CSI part 1, the first TRPand the fourth TRP are selected. In this example, some of L_(n)associated with the selected TRPs are explicitly reported and the othersare implicitly determined.

-   -   In one example, a joint indicator can be used to indicate        {Ln}_(n∈S\{n) _(Low) _(}) and L_(n) _(Low) is implicitly        determined by {Ln}_(n∈S\{n) _(Low) _(}) and L_(tot)=Σ_(n∈S)L_(n)        and L_(n)≥1 for n∈S\ {n_(Low)} where L_(n) is a positive integer        and S is a set of selected TRP indexes (i.e., a subset of {1,2,        . . . , N_(TRP)}) and n_(Low) is the lowest index in S.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n∈S\{n) _(Low) _(}) and L_(n) _(High) is implicitly        determined by {L_(n)}_(n∈S\{n) _(High) _(}) and        L_(tot)=Σ_(n∈S)L_(n) and L_(n)≥1 for n∈S\ {n_(High)} where L_(n)        is a positive integer and S is a set of selected TRP indexes        (i.e., a subset of {1,2, . . . , N_(TRP)}) and n_(High) is the        highest index in S.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n∈S\{n*}) and L_(n*) is implicitly determined by        {L_(n)}_(n∈S\{n*}) and L_(tot)=Σ_(n∈S)L_(n) and L_(n)≥1 for        n∈S\{n*} where L_(n) is a positive integer and S is a set of        selected TRP indexes (i.e., a subset of {1,2, . . . , N_(TRP)})        and n* is a reference TRP index in S, which can be determined by        UE or configured by NW or determined by a pre-defined rule.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n=1) ^(N-1) and LN is implicitly determined by        {L_(n)}_(n=1) ^(N-1) and L_(tot)=Σ_(n=1) ^(N)L_(n) and L_(n)≥1,        for n=1, . . . , N−1 where L_(n) is a positive integer.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n=2) ^(N) and L₁ is implicitly determined by {Ln}_(n=2)        ^(N) and L_(tot)=Σ_(n=1) ^(N) L_(n) and L_(n)≥1, for n=2, . . .        , N where L_(n) is a positive integer.    -   In one example, a joint indicator can be used to indicate        {L_(n)}_(n∈{1, . . . , N}∀{n*}) and L_(n*) is implicitly        determined by {L_(n)}_(n∈{1, . . . , N}∀{n*}) and        L_(tot)=Σ_(n=1) ^(N) L_(n) and L_(n)≥1, for n∈{1, . . . , N}        \{n*} where L_(n) is a positive integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈S\{n_(Low)} and L_(n) _(Low) is implicitly determined by        {L_(n)}_(n∈S\{n) _(Low) _(}) and L_(tot)=Σ_(n∈S) L_(n) and        L_(n)≥1 for n∈S\ {n_(Low)} where L_(n) is a positive integer and        S is a set of selected TRP indexes (i.e., a subset of {1,2, . .        . , N_(TRP)}) and n_(Low) is the lowest index in S.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈S\{n_(High)} and L_(n) _(High) is implicitly determined by        {Ln}_(n∈S\{n) _(High) _(}) and L_(tot)=Σ_(n∈S) L_(n) and L_(n)≥1        for n∈S\ {n_(High)} where L_(n) is a positive integer and S is a        set of selected TRP indexes (i.e., a subset of {1,2, . . . ,        N_(TRP)}) and n_(High) is the highest index in S.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈S\{n*} and L_(n) _({n*}) is implicitly determined by        {Ln}_(n∈S \{n*}) and L_(tot)=Σ_(n∈S)L_(n) and L_(n)≥1 for        n∈S\{n*} where L_(n) is a positive integer and S is a set of        selected TRP indexes (i.e., a subset of {1,2, . . . , N_(TRP)})        and n* is a reference TRP index in S, which can be determined by        UE or configured by NW or determined by a pre-defined rule.    -   In one example, an indicator can be used to indicate each L_(n)        for n=1, . . . , N−1 and L_(N) is implicitly determined by        {L_(n)}_(n=1) ^(N-1) and L_(tot)=Σ_(n=1) ^(N) L_(n) and L_(n)≥1,        for n=1, . . . , N−1 where L_(n) is a positive integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n=2, . . . , N and L₁ is implicitly determined by        {L_(n)}_(n=2) ^(N) and L_(tot)=Σ_(n=1) ^(N) L_(n) and L_(n)≥1,        for n=1, . . . , N−1 where L_(n) is a positive integer.    -   In one example, an indicator can be used to indicate each L_(n)        for n∈{1, . . . , N}\{n*} and L_(n*) is implicitly determined by        {L_(n)}_(n∈{1, . . . , N}\{n*}) and L_(tot)=Σ_(n=1) ^(N)L_(n)        and L_(n)≥1, for n∈{1, . . . , N} \{n*} where L_(n) is a        positive integer.

In one example, L_(n) SD basis vector selection for each TRP n isreported via a joint indicator or separate multiple indicators in CSIpart 2.

In one example, an indicator to indicate (each) L_(n) SD basis vectorshas the payload of

$\left\lceil {\log_{2}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits (bit-width), where N₁ and N₂ are the values of (N₁, N₂) configuredvia higher-layer (RRC) signaling by the NW, where n∈S or n=1, . . . , N.

-   -   In one example, a joint indicator to indicate {Ln} SD basis        vectors has the payload of

$\left\lceil {\log_{2}{\sum}_{n = 1}^{N}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits or

$\left\lceil {\log_{2}{\sum}_{n \in S}\begin{pmatrix}{N_{1}N_{2}} \\L_{n}\end{pmatrix}} \right\rceil$

bits.

In one example, some of L_(n)s associated with TRPs that are selectedare explicitly reported via a joint indicator or separate multipleindicators in CSI part 2 and the others of L_(n)s associated with TRPsthat are selected are reported implicitly (or determined implicitlyhence not explicitly reported). The remaining part is similar to otherexamples described herein.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N TRPs. The selection of L_(tot)SD basis vectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{NN_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 1. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each of the selected TRPs.

In one example, L_(tot) SD basis vectors are selected among allcandidates of SD basis vectors across N TRPs. The selection of L_(tot)SD basis vectors is reported via an indicator with size of

$\left\lceil {\log_{2}\begin{pmatrix}{NN_{1}N_{2}} \\L_{tot}\end{pmatrix}} \right\rceil$

bits in CSI part 2. In this case, L_(n) is implicitly determined bycounting the number of selected SD basis vectors that belong to thecandidate SD basis vectors of each of the selected TRPs.

In one embodiment, a bitmap with size of NN₁N₂ is used to indicate SDbasis vectors for selected N TRPs (CSI-RS resources) in CSI part 2. Forexample, in the bitmap, ‘0’ refers ‘not selected’ for corresponding SDvector and ‘1’ refers ‘selected’ for corresponding SD vector. In thiscase, L_(n) can be inferred from the bitmap, by counting the number ofselected SD vectors corresponding to each TRP. In this case, arestriction can be described such as “UE shall not report a CSI withL_(tot)=Σ_(n) L_(n)>L_(max), where L_(n) is inferred from the bitmap”.

In one embodiment, any combination or some of certain embodimentsdescribed herein can be configured by NW via higher-layer (RRC)signalling. In one example, any combination or some of examples inembodiments described herein can be configured by NW via higher-layerRRC signalling.

In one embodiment, in all embodiments/examples under a certainembodiment described herein, L_(n), L_(tot), L_(max) can be replaced byα_(n), α_(tot), α_(max), where

${\alpha_{n} = \frac{L_{n}}{N_{1}N_{2}}},{\alpha_{tot} = {\frac{L_{tot}}{N_{TRP}N_{1}N_{2}}\left( {{{or}\alpha_{tot}} = \frac{L_{tot}}{NN_{1}N_{2}}} \right)}},$${{and}\alpha_{\max}} = {\frac{L_{\max}}{N_{TRP}N_{1}N_{2}}{\left( {{{or}\alpha_{\max}} = \frac{L_{\max}}{NN_{1}N_{2}}} \right).}}$

FIG. 10 illustrates an example method 1000 performed by a UE in awireless communication system according to embodiments of the presentdisclosure. The method 1000 of FIG. 10 can be performed by any of theUEs 111-116 of FIG. 1 , such as the UE 116 of FIG. 3 , and acorresponding method can be performed by any of the BSs 101-103 of FIG.1 , such as BS 102 of FIG. 2 . The method 1000 is for illustration onlyand other embodiments can be used without departing from the scope ofthe present disclosure.

The method 1000 begins with the UE receiving information about a CSIreport (1010). For example, in 1010, the information can indicate N>1CSI-RS resources, a codebook, and codebook parameters. In this example,the codebook includes a SD basis component, a FD basis component, and acoefficient component. The SD basis component includes L_(r) basisvectors for each CSI-RS resource r=1, . . . , N. The FD basis componentincludes M_(v) basis vectors. The coefficient component includescoefficients associated with (SD, FD) basis vector pairs. The codebookparameters include

$p_{v} = \left\{ {\begin{matrix}{{\frac{1}{8}{for}v} = {1,2}} \\{{\frac{1}{16}{for}v} = {3,4}}\end{matrix},\left( {L_{1},L_{2},\ldots,L_{N}} \right),} \right.$

and β where p_(v) is a parameter to determine a value of M_(υ) based ona total number of precoding matrices N₃, v is a number of layers, andβ≤1 is a parameter to determine an upper bound K₀ of a number ofnon-zero coefficients of the coefficient component.

In various embodiments, when

${N = 2},{\beta = {{\frac{1}{4}{and}\left( {L_{1},L_{2}} \right)} = \left( {2,2} \right)}},$(L₁, L₂) = *2, 4), or(L₁, L₂) = (4, 2).

In another embodiment, when

${N = 2},{\beta = {{\frac{1}{2}{and}\left( {L_{1},L_{2}} \right)} = {\left( {4,4} \right).}}}$

In various embodiments, when

${N = 3},{\beta = {{\frac{1}{4}{or}\frac{1}{2}{and}\left( {L_{1},L_{2},L_{3}} \right)} = \left( {2,2,2} \right)}},$(L₁, L₂, L₃) = (2, 2, 4), (L₁, L₂, L₃) = (2, 4, 2),(L₁, L₂, L₃) = (4, 2, 2), or(L₁, L₂, L₃) = (4, 4, 4).

In various embodiments, when

${N = 4},{\beta = {{\frac{1}{4}{and}\left( {L_{1},L_{2},L_{3},L_{4}} \right)} = \left( {2,2,2,2} \right)}},$or(L₁, L₂, L₃, L₄) = (2, 2, 2, 4).

In another embodiment, when

${N = 4},{\beta = {{\frac{1}{2}{and}\left( {L_{1},L_{2},L_{3},L_{4}} \right)} = {\left( {4,4,4,4} \right).}}}$

The UE then measures the N CSI-RS resources (1020). For example, in1020, the measurement is based on the information received about the CSIreport. The UE then determines the SD basis component, the FD basiscomponent, and the coefficient component (1030). For example, in 1030,the determination may be based on the codebook parameters andinformation received about the CSI report. In various embodiments, thecodebook parameters further include L_(max), where L_(max)≥Σ_(r=1)^(N)L_(r). In one example, the UE further determines L_(r) for r=1, 2, .. . , N under a constraint of L_(max)≥Σ_(r=1) ^(N)L_(r), and the CSIreport further includes an indicator indicating L_(r) for r=1, 2, . . ., N.

The UE then transmits the CSI report (1040). For example, in 1040, theCSI report may include or indicate the determined SD basis component,the FD basis component, and the coefficient component.

Any of the above variation embodiments can be utilized independently orin combination with at least one other variation embodiment. The aboveflowcharts illustrate example methods that can be implemented inaccordance with the principles of the present disclosure and variouschanges could be made to the methods illustrated in the flowchartsherein. For example, while shown as a series of steps, various steps ineach figure could overlap, occur in parallel, occur in a differentorder, or occur multiple times. In another example, steps may be omittedor replaced by other steps.

Although the figures illustrate different examples of user equipment,various changes may be made to the figures. For example, the userequipment can include any number of each component in any suitablearrangement. In general, the figures do not limit the scope of thisdisclosure to any particular configuration(s). Moreover, while figuresillustrate operational environments in which various user equipmentfeatures disclosed in this patent document can be used, these featurescan be used in any other suitable system.

Although the present disclosure has been described with exemplaryembodiments, various changes and modifications may be suggested to oneskilled in the art. It is intended that the present disclosureencompasses such changes and modifications as falls within the scope ofthe appended claims. None of the descriptions in this application shouldbe read as implying that any particular element, step, or function is anessential element that must be included in the claims scope. The scopeof patented subject matter is defined by the claims.

What is claimed is:
 1. A user equipment (UE) comprising: a transceiver configured to receive information about a channel state information (CSI) report, the information indicating N>1 CSI reference signal (CSI-RS) resources and a codebook, wherein: the codebook includes a spatial-domain (SD) basis component, a frequency-domain (FD) basis component, and a coefficient component, the SD basis component includes L_(r) basis vectors for each CSI-RS resource r=1, . . . , N, the FD basis component includes M_(v) basis vectors, the coefficient component includes coefficients associated with (SD, FD) basis vector pairs, the information includes codebook parameters, and the codebook parameters include: $p_{v} = \left\{ {\begin{matrix} {{\frac{1}{8}{for}v} = {1,2}} \\ {{\frac{1}{16}{for}v} = {3,4}} \end{matrix},\left( {L_{1},L_{2},\ldots,L_{N}} \right),} \right.$  and β where: p_(v) is a parameter to determine a value of M_(v) based on a total number of precoding matrices N₃, v is a number of layers, and β≤1 is a parameter to determine an upper bound K₀ of a number of non-zero coefficients of the coefficient component; and a processor operably coupled to the transceiver, the processor, based on the information, configured to: measure the N CSI-RS resources, and determine, based on the codebook parameters, the SD basis component, the FD basis component, and the coefficient component, wherein the transceiver is further configured to transmit the CSI report.
 2. The UE of claim 1, wherein, when ${N = 2},{\beta = {\frac{1}{4}{and}}}$ (L₁, L₂) = (2, 2), (L₁, L₂) = (2, 4), or (L₁, L₂) = (4, 2).
 3. The UE of claim 1, wherein, when ${N = 2},{\beta = {{\frac{1}{2}{and}\left( {L_{1},L_{2}} \right)} = {\left( {4,4} \right).}}}$
 4. The UE of claim 1, wherein, when ${N = 3},{\beta = {\frac{1}{4}{or}\frac{1}{2}{and}}}$ (L₁, L₂, L₃) = (2, 2, 2), (L₁, L₂, L₃) = (2, 2, 4), (L₁, L₂, L₃) = (2, 4, 2), (L₁, L₂, L₃) = (4, 2, 2), or (L₁, L₂, L₃) = (4, 4, 4).
 5. The UE of claim 1, wherein, when ${N = 4},{\beta = {\frac{1}{4}{and}}}$ (L₁, L₂, L₃, L₄) = (2, 2, 2, 2), or (L₁, L₂, L₃, L₄) = (2, 2, 2, 4).
 6. The UE of claim 1, wherein, when ${N = 4},{\beta = {{\frac{1}{2}{and}\left( {L_{1},L_{2},L_{3},L_{4}} \right)} = {\left( {4,4,4,4} \right).}}}$
 7. The UE of claim 1, wherein the codebook parameters further include L_(max), where L_(max)≥Σ_(r=1) ^(N)L_(r).
 8. The UE of claim 7, wherein: the processer is further configured to determine L_(r) for r=1, 2, . . . , N under a constraint of L_(max)≥Σ_(r=1) ^(N)L_(r), and the CSI report further includes an indicator indicating L_(r) for r=1, 2, . . . , N.
 9. A base station (BS) comprising: a processor configured to identify information about a channel state information (CSI) report, the information indicating N>1 CSI reference signal (CSI-RS) resources and a codebook, wherein: the codebook includes a spatial-domain (SD) basis component, a frequency-domain (FD) basis component, and a coefficient component, the SD basis component includes L_(r) basis vectors for each CSI-RS resource r=1, . . . , N, the FD basis component includes M_(v) basis vectors, the coefficient component includes coefficients associated with (SD, FD) basis vector pairs, the information includes codebook parameters, and the codebook parameters include: $p_{v} = \left\{ {\begin{matrix} {{\frac{1}{8}{for}v} = {1,2}} \\ {{\frac{1}{16}{for}v} = {3,4}} \end{matrix},\left( {L_{1},L_{2},\ldots,L_{N}} \right),} \right.$  and β where: p_(v) is a parameter to determine a value of M_(v) based on a total number of precoding matrices N₃, V is a number of layers, and β≤1 is a parameter to determine an upper bound K₀ of a number of non-zero coefficients of the coefficient component; and a transceiver operably coupled to the processor, the transceiver configured to: transmit the information about the CSI report, and receive the CSI report.
 10. The BS of claim 9, wherein, when ${N = 2},{\beta = {\frac{1}{4}{and}}}$ (L₁, L₂) = (2, 2), (L₁, L₂) = (2, 4), or (L₁, L₂) = (4, 2).
 11. The BS of claim 9, wherein, when ${N = 2},{\beta = {{\frac{1}{2}{and}\left( {L_{1},L_{2}} \right)} = {\left( {4,4} \right).}}}$
 12. The BS of claim 9, wherein, when ${N = 3},{\beta = {\frac{1}{4}{or}\frac{1}{2}{and}}}$ (L₁, L₂, L₃) = (2, 2, 2), (L₁, L₂, L₃) = (2, 2, 4), (L₁, L₂, L₃) = (2, 4, 2), (L₁, L₂, L₃) = (4, 2, 2), or (L₁, L₂, L₃) = (4, 4, 4).
 13. The BS of claim 9, wherein, when ${N = 4},{\beta = {\frac{1}{4}{and}}}$ (L₁, L₂, L₃, L₄) = (2, 2, 2, 2), or (L₁, L₂, L₃, L₄) = (2, 2, 2, 4).
 14. The BS of claim 9, wherein, when ${N = 4},{\beta = {{\frac{1}{2}{and}\left( {L_{1},L_{2},L_{3},L_{4}} \right)} = {\left( {4,4,4,4} \right).}}}$
 15. The BS of claim 9, wherein the codebook parameters further include L_(max), where L_(max)≥Σ_(r=1) ^(N)=1L_(r).
 16. The BS of claim 15, wherein: L_(r) for r=1, 2, . . . , N is under a constraint of L_(max)≥Σ_(r=1) ^(N)L_(r), and the CSI report further includes an indicator indicating L_(r) for r=1, 2, . . . , N.
 17. A method performed by a user equipment (UE), the method comprising: receiving information about a channel state information (CSI) report, the information indicating N>1 CSI reference signal (CSI-RS) resources and a codebook, wherein: the codebook includes a spatial-domain (SD) basis component, a frequency-domain (FD) basis component, and a coefficient component, the SD basis component includes L_(r) basis vectors for each CSI-RS resource r=1, . . . , N, the FD basis component includes M_(v) basis vectors, the coefficient component includes coefficients associated with (SD, FD) basis vector pairs, the information includes codebook parameters, and the codebook parameters include: $p_{v} = \left\{ {\begin{matrix} {{\frac{1}{8}{for}v} = {1,2}} \\ {{\frac{1}{16}{for}v} = {3,4}} \end{matrix},\left( {L_{1},L_{2},\ldots,L_{N}} \right),} \right.$  and β where: p_(v) is a parameter to determine a value of M_(v) based on a total number of precoding matrices N₃, v is a number of layers, and β≤1 is a parameter to determine an upper bound K₀ of a number of non-zero coefficients of the coefficient; based on the information, measuring the N CSI-RS resources; determining, based on the codebook parameters, the SD basis component, the FD basis component, and the coefficient component; and transmitting the CSI report.
 18. The method of claim 17, wherein, when ${N = 2},{\beta = {\frac{1}{4}{and}}}$ (L₁, L₂) = (2, 2), (L₁, L₂) = (2, 4), or (L₁, L₂) = (4, 2).
 19. The method of claim 17, wherein, when ${N = 2},{\beta = {{\frac{1}{2}{and}\left( {L_{1},L_{2}} \right)} = {\left( {4,4} \right).}}}$
 20. The method of claim 17, wherein, when ${N = 3},{\beta = {\frac{1}{4}{or}\frac{1}{2}{and}}}$ (L₁, L₂, L₃) = (2, 2, 2), (L₁, L₂, L₃) = (2, 2, 4), (L₁, L₂, L₃) = (2, 4, 2), (L₁, L₂, L₃) = (4, 2, 2), or (L₁, L₂, L₃) = (4, 4, 4). 